Search results for: depth images

Authors: Leping Chen, Daoxiang An, Xiaotao Huang

Abstract:

Automatic vehicle detection using synthetic aperture radar (SAR) image has been widely researched, as well as using optical remote sensing images. However, most researches treat the detection as an independent problem, failing to make full use of SAR data information. In circular SAR (CSAR), the two long borders of vehicle will shrink if the imaging surface is set higher than the reference one. Based on above variance, an automatic vehicle detection using CSAR image is proposed to enhance detection ability under complex environment, such as vehicles’ closely packing, which confuses the detector. The detection method uses the multiple images generated by different height plane to obtain an energy-concentrated image for detecting and then uses the maximally stable extremal regions method (MSER) to detect vehicles. A result of vehicles’ detection is given to verify the effectiveness and correctness of proposed method.

Keywords: circular SAR, vehicle detection, automatic, imaging

Procedia PDF Downloads 362

Authors: Osama A. Terfas, Abdelhakim A. Hameda, Abdusalam A. Alktiwi

Abstract:

An investigation on ductile crack growth of shallow semi-elliptical surface cracks with a/w=0.2, a/c=0.33 under bending was carried out, where a is the crack depth, w is the plate thickness and c is the crack length at surface. Finite element analysis and experiments were modelling and the crack growth model were verified with experimental data. The results showed that the initial crack shape was no longer maintained as the crack developed under ductile tearing. The maximum growth at the deepest point at early stages was stopped when the crack depth reached half thickness and growth occurred beneath surface. Excellent agreement in the crack shape patterns was observed between the experiments and the crack growth model.

Keywords: crack growth, ductile tearing, mean stress, surface cracks

Procedia PDF Downloads 482

Authors: D. Heinemann, S. Schramm, S. Knabner, D. Baumgarten

Abstract:

Purpose: Applying solder paste to printed circuit boards (PCB) with stencils has been the method of choice over the past years. A new method uses a jet printer to deposit tiny droplets of solder paste through an ejector mechanism onto the board. This allows for more flexible PCB layouts with smaller components. Due to the viscosity of the solder paste, air blisters can be trapped in the cartridge. This can lead to missing solder joints or deviations in the applied solder volume. Therefore, a built-in and real-time inspection of the printing process is needed to minimize uncertainties and increase the efficiency of the process by immediate correction. The objective of the current study is the design of an optimal imaging system and the development of an automatic algorithm for the detection of applied solder joints from optical from the captured images. Methods: In a first approach, a camera module connected to a microcomputer and LED strips are employed to capture images of the printed circuit board under four different illuminations (white, red, green and blue). Subsequently, an improved system including a ring light, an objective lens, and a monochromatic camera was set up to acquire higher quality images. The obtained images can be divided into three main components: the PCB itself (i.e., the background), the reflections induced by unsoldered positions or screw holes and the solder joints. Non-uniform illumination is corrected by estimating the background using a morphological opening and subtraction from the input image. Image sharpening is applied in order to prevent error pixels in the subsequent segmentation. The intensity thresholds which divide the main components are obtained from the multimodal histogram using three probability density functions. Determining the intersections delivers proper thresholds for the segmentation. Remaining edge gradients produces small error areas which are removed by another morphological opening. For quantitative analysis of the segmentation results, the dice coefficient is used. Results: The obtained PCB images show a significant gradient in all RGB channels, resulting from ambient light. Using different lightings and color channels 12 images of a single PCB are available. A visual inspection and the investigation of 27 specific points show the best differentiation between those points using a red lighting and a green color channel. Estimating two thresholds from analyzing the multimodal histogram of the corrected images and using them for segmentation precisely extracts the solder joints. The comparison of the results to manually segmented images yield high sensitivity and specificity values. Analyzing the overall result delivers a Dice coefficient of 0.89 which varies for single object segmentations between 0.96 for a good segmented solder joints and 0.25 for single negative outliers. Conclusion: Our results demonstrate that the presented optical imaging system and the developed algorithm can robustly detect solder joints on printed circuit boards. Future work will comprise a modified lighting system which allows for more precise segmentation results using structure analysis.

Keywords: printed circuit board jet-printing, inspection, segmentation, solder paste detection

Procedia PDF Downloads 332

Authors: Jin Song Gui, Han Li, Rui Jin Zhang, Heng Jiang Cai

Abstract:

There is a large deviation between the measured wave power at the vertical breast wall and the calculated one according to current specification in the case of overtopping. In order to investigate the reasons for the deviation, the wave forces of vertical breast wall under overtopping conditions have been measured through physical model experiment and compared with the calculated results. The effect of water depth, period and the wave height on the wave forces of the vertical breast wall have been also investigated. The distribution of wave pressure under different wave actions was tested based on the force sensor which is installed in the vertical breakwater. By comparing and analyzing the measured values and norms calculated values, the applicability of the existing norms recommended method were discussed and a reference for the design of vertical breakwater was provided. Experiment results show that with the decrease of the water depth, the gap is growing between the actual wave forces and the specification values, and there are no obvious regulations between these two values with the variation of period while wave force greatly reduces with the overtopping reducing. The amount of water depth and wave overtopping has a significant impact on the wave force of overtopping section while the period has no obvious influence on the wave force. Finally, some favorable recommendations for the overtopping wave force design of the vertical breakwater according to the model experiment results are provided.

Keywords: overtopping wave, physical model experiment, vertical breakwater, wave forces

Procedia PDF Downloads 301

Authors: Calorine Twebaze, Jesca Balinga

Abstract:

Field X is located on the Eastern shores of L. Albert, Uganda, on the rift flank where the gross sedimentary fill is typically less than 2,000m. The field was discovered in 2006 and encountered about 20.4m of net pay across three (3) stratigraphic intervals within the discovery well. The field covers an area of 3 km2, with the structural configuration comprising a 3-way dip-closed hanging wall anticline that seals against the basement to the southeast along the bounding fault. Field X had been mapped on reprocessed 3D seismic data, which was originally acquired in 2007 and reprocessed in 2013. The seismic data quality is good across the field, and reprocessing work reduced the uncertainty in the location of the bounding fault and enhanced the lateral continuity of reservoir reflectors. The current study was a re-evaluation of Field X to refine fault interpretation and understand the structural uncertainties associated with the field. The seismic data, and three (3) wells datasets were used during the study. The evaluation followed standard workflows using Petrel software and structural attribute analysis. The process spanned from seismic- -well tie, structural interpretation, and structural uncertainty analysis. Analysis of three (3) well ties generated for the 3 wells provided a geophysical interpretation that was consistent with geological picks. The generated time-depth curves showed a general increase in velocity with burial depth. However, separation in curve trends observed below 1100m was mainly attributed to minimal lateral variation in velocity between the wells. In addition to Attribute analysis, three velocity modeling approaches were evaluated, including the Time-Depth Curve, Vo+ kZ, and Average Velocity Method. The generated models were calibrated at well locations using well tops to obtain the best velocity model for Field X. The Time-depth method resulted in more reliable depth surfaces with good structural coherence between the TWT and depth maps with minimal error at well locations of 2 to 5m. Both the NNE-SSW rift border fault and minor faults in the existing interpretation were reevaluated. However, the new interpretation delineated an E-W trending fault in the northern part of the field that had not been interpreted before. The fault was interpreted at all stratigraphic levels and thus propagates from the basement to the surface and is an active fault today. It was also noted that the entire field is less faulted with more faults in the deeper part of the field. The major structural uncertainties defined included 1) The time horizons due to reduced data quality, especially in the deeper parts of the structure, an error equal to one-third of the reflection time thickness was assumed, 2) Check shot analysis showed varying velocities within the wells thus varying depth values for each well, and 3) Very few average velocity points due to limited wells produced a pessimistic average Velocity model.

Keywords: 3D seismic data interpretation, structural uncertainties, attribute analysis, velocity modelling approaches

Procedia PDF Downloads 53

Authors: Frederick W. Gooding, Jr., Mark Beeman

Abstract:

Nearly a century ago, the groundbreaking 1915 film ‘The Birth of a Nation’ popularized the way Hollywood made movies with its avant-garde, feature-length style. The movie's subjugating and demeaning depictions of African American women (and men) reflected popular racist beliefs held during the time of slavery and the early Jim Crow era. Although much has changed concerning race relations in the past century, American sociologist Patricia Hill Collins theorizes that the disparaging images of African American women originating in the era of plantation slavery are adaptable and endure as controlling images today. In this context, a comparative analysis of the successful contemporary film, ‘Bringing Down the House’ starring Queen Latifah is relevant as this 2004 film was designed to purposely defy and ridicule classic stereotypes of African American women. However, the film is still tied to the controlling images from the past, although in a modern hybrid form. Scholars of race and film have noted that the pervasive filmic imagery of the African American woman as the loyal mammy stereotype faded from the screen in the post-civil rights era in favor of more sexualized characters (i.e., the Jezebel trope). Analyzing scenes and dialogue through the lens of sociological and critical race theory, the troubling persistence of African American controlling images in film stubbornly emerge in a movie like ‘Bringing Down the House.’ Thus, these controlling images, like racism itself, can adapt to new social and economic conditions. Although the classic controlling images appeared in the first feature length film focusing on race relations a century ago, ‘The Birth of a Nation,’ this black and white rendition of the mammy figure was later updated in 1939 with the classic hit, ‘Gone with the Wind’ in living color. These popular controlling images have loomed quite large in the minds of international audiences, as ‘Gone with the Wind’ is still shown in American theaters currently, and experts at the British Film Institute in 2004 rated ‘Gone with the Wind’ as the number one movie of all time in UK movie history based upon the total number of actual viewings. Critical analysis of character patterns demonstrate that images that appear superficially benign contribute to a broader and quite persistent pattern of marginalization within the aggregate. This approach allows experts and viewers alike to detect more subtle and sophisticated strands of racial discrimination that are ‘hidden in plain sight’ despite numerous changes in the Hollywood industry that appear to be more voluminous and diverse than three or four decades ago. In contrast to white characters, non-white or minority characters are likely to be subtly compromised or marginalized relative to white characters if and when seen within mainstream movies, rather than be subjected to obvious and offensive racist tropes. The hybrid form of both the older Jezebel and Mammy stereotypes exhibited by lead actress Queen Latifah in ‘Bringing Down the House’ represents a more suave and sophisticated merging of past imagery ideas deemed problematic in the past as well as the present.

Keywords: African Americans, Hollywood film, hybrid, stereotypes

Procedia PDF Downloads 173

Authors: J. L. Liu, L. Wang, B. Zhu, J. Zhou, W. D. Gao

Abstract:

Fabric textures are very common in our daily life. However, we never explore the representation of fabric textures from neuroscience view. Theoretical studies suggest that primary visual cortex (V1) uses a sparse code to efficiently represent natural images. However, how the simple cells in V1 encode the artificial textures is still a mystery. So, here we will take fabric texture as stimulus to study the response of independent component analysis that is established to model the receptive field of simple cells in V1. Experimental results based on 140 classical fabric images indicate that the receptive fields of simple cells have obvious selectivity in orientation, frequency, and phase when drifting gratings are used to determine their tuning properties. Additionally, the distribution of optimal orientation and frequency shows that the patch size selected from each original fabric image has a significant effect on the frequency selectivity.

Keywords: fabric texture, receptive filed, simple cell, spare coding

Procedia PDF Downloads 467

Authors: Adel Edwar Waheeb Louka

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

Procedia PDF Downloads 62

Authors: Ebenezer Obaloluwa Olaniyi

Abstract:

In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

Procedia PDF Downloads 394

Authors: Faijal Ali, Darga Kumar N., Ravikant Singh, Rajnil Lal

Abstract:

Fiji has three major landforms such as plains, low mountains, and hills. The low land soils are formed on beach sand. Fiji soils contain high concentration of iron (III), aluminum oxides and hydroxides. The soil possesses reddish or yellowish colour. The characterization of lateritic soils collected from different locations along the national highway in Viti Levu, Fiji Islands. The research has been carried out mainly to understand the physical and strength properties to assess their suitability for the highway and building construction. In this paper, the field tests such as dynamic cone penetrometer test, field vane shear, field density and laboratory tests such as unconfined compression stress, compaction, grain size analysis and Atterberg limits are conducted. The test results are analyzed and presented. From the results, it is revealed that the soils are having more percentage of silt and clay which is more than 80% and 5 to 15% of fine to medium sand is noticed. The dynamic cone penetrometer results up to 3m depth had similar penetration resistance. For the first 1m depth, the rate of penetration is found 300mm per 3 to 4 blows. In all the sites it is further noticed that the rate of penetration at depths beyond 1.5 m is decreasing for the same number of blows as compared to the top soil. From the penetration resistance measured through dynamic cone penetrometer test, the California bearing ratio and allowable bearing capacities are 4 to 5% and 50 to 100 kPa for the top 1m layer and below 1m these values are increasing. The California bearing ratio of these soils for below 1m depth is in the order of 10% to 20%. The safe bearing capacity of these soils below 1m and up to 3m depth is varying from 150 kPa to 250 kPa. The field vane shear was measured within a depth of 1m from the surface and the values were almost similar varying from 60 kPa to 120 kPa. The liquid limit and plastic limits of these soils are in the range of 40 to 60% and 20 to 25%. Overall it is found that the top 1m soil along the national highway in majority places possess a soft to medium stiff behavior with low to medium bearing capacity as well low California bearing ratio values. It is recommended to ascertain these soils behavior in terms of geotechnical parameters before taking up any construction activity.

Keywords: California bearing ratio, dynamic cone penetrometer test, field vane shear, unconfined compression stress.

Procedia PDF Downloads 183

Authors: Y. C. Khoo, W. T. Lai

Abstract:

The single orifice hydraulic flat spray nozzle was evaluated with two global imaging techniques to characterize various aspects of the resulting spray. The two techniques were high resolution flow visualization and Particle Image Velocimetry (PIV). A CCD camera with 29 million pixels was used to capture shadowgraph images to realize ligament formation and collapse as well as droplet interaction. Quantitative analysis was performed to give the sizing information of the droplets and ligaments. This camera was then applied with a PIV system to evaluate the overall velocity field of the spray, from nozzle exit to droplet discharge. PIV images were further post-processed to determine the inclusion angle of the spray. The results from those investigations provided significant quantitative understanding of the spray structure. Based on the quantitative results, detailed understanding of the spray behavior was achieved.

Keywords: spray, flow visualization, PIV, shadowgraph, quantitative sizing, velocity field

Procedia PDF Downloads 377

Authors: Nuraddeen Usman, Khiruddin Abdullah, Mohd Nawawi, Amin Khalil Ismail

Abstract:

A magnetic survey is carried out in order to locate the remains of construction items, specifically concrete pillars. The conventional Euler deconvolution technique can perform the task but it requires the use of fixed structural index (SI) and the construction items are made of materials with different shapes which require different SI (unknown). A Euler deconvolution technique that estimate background, horizontal coordinate (xo and yo), depth and structural index (SI) simultaneously is prepared and used for this task. The synthetic model study carried indicated the new methodology can give a good estimate of location and does not depend on magnetic latitude. For field data, both the total magnetic field and gradiometer reading had been collected simultaneously. The computed vertical derivatives and gradiometer readings are compared and they have shown good correlation signifying the effectiveness of the method. The filtering is carried out using automated procedure, analytic signal and other traditional techniques. The clustered depth solutions coincided with the high amplitude/values of analytic signal and these are the possible target positions of the concrete pillars being sought. The targets under investigation are interpreted to be located at the depth between 2.8 to 9.4 meters. More follow up survey is recommended as this mark the preliminary stage of the work.

Keywords: concrete pillar, magnetic survey, geotechnical investigation, Euler Deconvolution

Procedia PDF Downloads 255

Authors: Ksheeraj Sai Vepuri, Nada Attar

Abstract:

We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

Procedia PDF Downloads 138

Authors: Soumya Sajjan

Abstract:

Liver cancer is the most common cancer disease worldwide in men and women, and is one of the few cancers still on the rise. Liver disease is the 4th leading cause of death. According to new NHS (National Health Service) figures, deaths from liver diseases have reached record levels, rising by 25% in less than a decade; heavy drinking, obesity, and hepatitis are believed to be behind the rise. In this study, we focus on Development of Diagnostic Classifier for Ultrasound liver lesion. Ultrasound (US) Sonography is an easy-to-use and widely popular imaging modality because of its ability to visualize many human soft tissues/organs without any harmful effect. This paper will provide an overview of underlying concepts, along with algorithms for processing of liver ultrasound images Naturaly, Ultrasound liver lesion images are having more spackle noise. Developing classifier for ultrasound liver lesion image is a challenging task. We approach fully automatic machine learning system for developing this classifier. First, we segment the liver image by calculating the textural features from co-occurrence matrix and run length method. For classification, Support Vector Machine is used based on the risk bounds of statistical learning theory. The textural features for different features methods are given as input to the SVM individually. Performance analysis train and test datasets carried out separately using SVM Model. Whenever an ultrasonic liver lesion image is given to the SVM classifier system, the features are calculated, classified, as normal and diseased liver lesion. We hope the result will be helpful to the physician to identify the liver cancer in non-invasive method.

Keywords: segmentation, Support Vector Machine, ultrasound liver lesion, co-occurance Matrix

Procedia PDF Downloads 404

Authors: Hichem Sassi

Abstract:

Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

Procedia PDF Downloads 57

Authors: Muhammad Ali, Zeeshan Afzal, Giampaolo Ferraioli, Gilda Schirinzi, Muhammad Saleem Mughal, Vito Pascazio

Abstract:

On 24 September 2019, an earthquake with 5.6 Mw and 10 km depth stroke in Mirpur. The Mirpur area was highly affected by this earthquake, with the death of 34 people. This study aims to estimate the surface deformation associated with this earthquake. The interferometric synthetic aperture radar (InSAR) technique is applied to study earthquake induced surface motion. InSAR data using 9 Sentinel-1A SAR images from 11 August 2019 to 22 October 2019 is used to investigate the pre, co-, and post-seismic deformation trends. Time series investigation reveals that there was not such deformation in pre-seismic time period. In the co-seismic time period, strong displacement was observed, and in post-seismic results, small displacement is seen due to aftershocks. Our results show the existence of a previously unpublished blind fault in Mirpur and help to locate the fault line. Previous this fault line was triggered during the 2005 earthquake, and now it’s activated on 24 September 2019. Study area is already facing many problems due to natural hazards where additional surface deformations, particularly because of an earthquake with an activated blind fault, have increased its vulnerability.

Keywords: surface deformation, InSAR, earthquake, sentinel-1, mirpur

Procedia PDF Downloads 124

Authors: Konstantinos C. Kartsakalis, Angeliki Skoura, Vasileios Megalooikonomou

Abstract:

The fuzzy composition of objects depicted in images acquired through MR imaging or the use of bio-scanners has often been a point of controversy for field experts attempting to effectively delineate between the visualized objects. Modern approaches in medical image segmentation tend to consider fuzziness as a characteristic and inherent feature of the depicted object, instead of an undesirable trait. In this paper, a novel technique for efficient image retrieval in the context of images in which segmented objects are either crisp or fuzzily bounded is presented. Moreover, the proposed method is applied in the case of multiple, even conflicting, segmentations from field experts. Experimental results demonstrate the efficiency of the suggested method in retrieving similar objects from the aforementioned categories while taking into account the fuzzy nature of the depicted data.

Keywords: fuzzy object, fuzzy image segmentation, motion descriptors, MRI imaging, object-based image retrieval

Procedia PDF Downloads 370

Authors: Peter U. Eze, P. Udaya, Robin J. Evans

Abstract:

Data hiding can be achieved by Steganography or invisible digital watermarking. For digital watermarking, both accurate retrieval of the embedded watermark and the integrity of the cover image are important. Medical image security in Teleradiology is one of the applications where the embedded patient record needs to be extracted with accuracy as well as the medical image integrity verified. In this research paper, the Constant Correlation Spread Spectrum digital watermarking for medical image tamper detection and accurate embedded watermark retrieval is introduced. In the proposed method, a watermark bit from a patient record is spread in a medical image sub-block such that the correlation of all watermarked sub-blocks with a spreading code, W, would have a constant value, p. The constant correlation p, spreading code, W and the size of the sub-blocks constitute the secret key. Tamper detection is achieved by flagging any sub-block whose correlation value deviates by more than a small value, ℇ, from p. The major features of our new scheme include: (1) Improving watermark detection accuracy for high-pixel depth medical images by reducing the Bit Error Rate (BER) to Zero and (2) block-level tamper detection in a single computational process with simultaneous watermark detection, thereby increasing utility with the same computational cost.

Keywords: Constant Correlation, Medical Image, Spread Spectrum, Tamper Detection, Watermarking

Procedia PDF Downloads 185

Authors: M. Alkhalidi, S. Neelamani, Z. Al-Zaqah

Abstract:

This paper investigates the interaction of single and twin offshore rubble mound breakwaters with regular and random water waves through physical modeling to assess their reflection, transmission and energy dissipation characteristics. Various combinations of wave heights and wave periods were utilized in a series of experiments, along with three different water depths. The single and twin permeable breakwater models were both constructed with one layer of rubbles. Both models had the same total volume; however, the single breakwater was of trapezoidal type while the twin breakwaters were of triangular type. Physical modeling experiments were carried out in the wave flume of the coastal engineering laboratory of Kuwait Institute for Scientific Research (KISR). Measurements of the six wave probes which were fixed in the two-dimensional wave flume were collected and used to determine the generated incident wave heights, as well as the reflected and transmitted wave heights resulting from the wave-breakwater interaction. The possible factors affecting the wave attenuation efficiency of the breakwater models are the relative water depth (d/L), wave steepness (H/L), relative wave height ((h-d)/Hi), relative height of the breakwater (h/d), and relative clear spacing between the twin breakwaters (S/h). The results indicated that the single and double breakwaters show different responds to the change in their relative height as well as the relative wave height which demonstrates that the effect of the relative water depth on wave reflection, transmission, and energy dissipation is highly influenced by the change in the relative breakwater height, the relative wave height and the relative breakwater spacing. In general, within the range of the relative water depth tested in this study, and under both regular and random waves, it is found that the single breakwater allows for lower wave transmission and shows higher energy dissipation effect than both of the tested twin breakwaters, and hence has the best overall performance.

Keywords: random waves, regular waves, relative water depth, relative wave height, single breakwater, twin breakwater, wave steepness

Procedia PDF Downloads 319

Authors: Shaymaa Kennedy, Sam Clark, Paul Shaply

Abstract:

With the upcoming construction of high-speed rail HS2 in the UK, a number of issues surrounding the construction technology and track design need to be answered. In this paper performance of subsoil subjected to dynamic loads were studied. The material of study is Mudrock backfill, a weak prevalent rock which response under indicative loading of high-speed rail line is unknown. This paper aims to investigate the use of different track types and the influence they will have on the underlying soil, in order to evaluate the behaviour of it. Ballstless track is a well-established concept in Europe, and the investigation the benefit of the form of construction due to its known savings in maintenance costs. Physical test using a triaxial cyclic loading machine was conducted to assess the expected mechanical behaviour of mudrock under a range of dynamic loads which could be generated beneath different track constructions. Some further parameters are required to frame the problem including determining the stress change with depth and cyclic response are vital to determine the residual plastic strain which is a major concern. In addition, Stress level is discussed in this paper, which are applied to recreate conditions of soil in the laboratory. Results indicate that stress levels are highly influential on the performance of soil at shallower depth and become insignificant with increasing depth.

Keywords: stress level, dynamic load, residual plastic strain, high speed railway

Procedia PDF Downloads 244

Authors: Maria Nejjari, Michel Cloutier, Guylaine Talbot, Martin Lanthier

Abstract:

The fluorescence in situ hybridization (FISH) is a staining technique that allows the identification, detection and quantification of microorganisms without prior cultivation by means of epifluorescence and confocal laser scanning microscopy (CLSM). Oligonucleotide probes have been used to detect bacteria and archaea that colonize the cattle and swine digestive systems. These bacterial strains have been obtained from fecal samples issued from cattle manure and swine slurry. The collection of these samples has been done at 3 different pit’s levels A, B and C with same height. Two collection depth levels have been taken in consideration, one collection level just under the pit’s surface and the second one at the bottom of the pit. Cells were fixed and FISH was performed using oligonucleotides of 15 to 25 nucleotides of length associated with a fluorescent molecule Cy3 or Cy5. The double hybridization using Cy3 probe targeting bacteria (Cy3-EUB338-I) along with a Cy5 probe targeting Archaea (Gy5-ARCH915) gave a better signal. The CLSM images show that there are more bacteria than archaea in swine slurry. However, the choice of fluorescent probes is critical for getting the double hybridization and a unique signature for each microorganism. FISH technique is an easy way to detect pathogens like E. coli O157, Listeria, Salmonella that easily contaminate water streams, agricultural soils and, consequently, food products and endanger human health.

Keywords: archaea, bacteria, detection, FISH, fluorescence

Procedia PDF Downloads 384

Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

Abstract:

River is the main source of water. It is a form of natural open channel which gives rise to many complex phenomenon of sciences that needs to be tackled such as the critical flow conditions, boundary shear stress and depth averaged velocity. The development of society more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, Conveyance Estimation System (CES) software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel and the results are compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth , velocity distribution

Procedia PDF Downloads 117

Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

Abstract:

Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

Procedia PDF Downloads 129

Authors: A. Nachour, L. Ouzizi, Y. Aoura

Abstract:

Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: edge detection, medical MRImages, multi-agent systems, vector field convolution

Procedia PDF Downloads 388

Authors: Shweta Pinjarkar, Shrutika Yawale, Mayuri Patil, Reshma Adagale

Abstract:

Face recognition is the technique which can be applied to the wide variety of problems like image and film processing, human computer interaction, criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are easy and simple to implement. In this, demonstrates the face recognition system in android device using eigenface. The system can be used as the base for the development of the recognition of human identity. Test images and training images are taken directly with the camera in android device.The test results showed that the system produces high accuracy. The goal is to implement model for particular face and distinguish it with large number of stored faces. face recognition system detects the faces in picture taken by web camera or digital camera and these images then checked with training images dataset based on descriptive features. Further this algorithm can be extended to recognize the facial expressions of a person.recognition could be carried out under widely varying conditions like frontal view,scaled frontal view subjects with spectacles. The algorithm models the real time varying lightning conditions. The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions using android application. Face recognition is the technique which can be applied to the wide variety of problems like image and film processing, human computer interaction, criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are easy and simple to implement. In this , demonstrates the face recognition system in android device using eigenface. The system can be used as the base for the development of the recognition of human identity. Test images and training images are taken directly with the camera in android device.The test results showed that the system produces high accuracy. The goal is to implement model for particular face and distinguish it with large number of stored faces. face recognition system detects the faces in picture taken by web camera or digital camera and these images then checked with training images dataset based on descriptive features. Further this algorithm can be extended to recognize the facial expressions of a person.recognition could be carried out under widely varying conditions like frontal view,scaled frontal view subjects with spectacles. The algorithm models the real time varying lightning conditions. The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions using android application.

Keywords: face detection, face recognition, eigen faces, algorithm

Procedia PDF Downloads 355

Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

Abstract:

Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

Procedia PDF Downloads 420

Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

Abstract:

The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

Procedia PDF Downloads 135

Authors: Sunil Kumar Singal, Manoj Sood, Upendra Bajpai

Abstract:

Instream technology is the upcoming sustainable approach in the hydro sector for energy harnessing. With well-known cross-sections and regulated supply, open channels are the most prominent locations for the installation of hydrokinetic turbines. The fluctuation in generated torque varies with site condition (flow depth and flow velocity), as well as with the type of turbine. The present experimental study aims to investigate the torque/power fluctuations of crossflow hydrokinetic turbines operating at different flow velocities and water depths. The flow velocity is varied from 1.0 m/s to 2.0 m/s. The complete assembly includes an open channel having dimensions of 0.3 m (depth) x 0.71 m (width) x 4.5 m (length), along with a lifting mechanism for varying the channel slope, a digital transducer for monitoring the torque, power, and rpm, a digital handheld water velocity meter for measuring the flow velocity. Further, a time series of torque, power, and rpm is plotted for a duration of 30 minutes showing the continuous operation of the turbine. A comparison of Savonius, Darrieus, and their improved twisted and helical blades is also presented in the study. A correlation has also been developed for assessing the hydropower generation from the installed turbine. The developed correlations will be very useful in the decision-making process for development at a site.

Keywords: darrieus turbine, flow velocity, open channel, savoinus turbine, water depth, hydropower

Procedia PDF Downloads 78

Authors: Mohammad Reza Haji Babai, Sepideh Ahmadkhan Beigi

Abstract:

Internationalization and modernization of the globe have played their roles in the process of cultural interaction between globalized societies and, consequently, found their way to the world of literature under the name of ‘imagology’. Imagology has made it possible for the reader to understand the author’s thoughts and judgments of others. The present research focuses on the intercultural images portrayed in the novel of a popular Turkish-French writer, Elif Shafak, about the lifestyle, traditions, habits, and social norms of Turkish, Americans, and Armenians. The novel seeks to articulate a more intricate multicultural memory of Turkishness by grieving over the Armenian massacre. This study finds that, as a mixture of multiple lifestyles and discourses, The Bastard of Istanbul reflects not only images of oriental culture but also occidental cultures. This means that the author has attempted to maintain selfhood through historical and cultural recollection, which resulted in constructing the self and another identity.

Keywords: imagology, Elif Shafak, The Bastard of Istanbul, self-image, other-image

Procedia PDF Downloads 139

Authors: Tarek S. Duzan, Fisal Ben Ammer, Mohamed Sula

Abstract:

In some places within Sirt Basin-Libya, it has been noticed that seismic data below pre-upper cretaceous unconformity (PUK) is hopeless to resolve the large-scale structural features and is unable to fully determine reservoir delineation. Seismic artifacts (multiples) are observed in the reservoir zone (Nubian Formation) below PUK, which complicate the process of seismic interpretation. The nature of the unconformity and the structures below are still ambiguous and not fully understood which generates a significant gap in characterizing the geometry of the reservoir, the uncertainty accompanied with lack of reliable seismic data creates difficulties in building a robust geological model. High resolution dipmeter is highly useful in steeply dipping zones. This paper uses FMl and OBMl borehole images (dipmeter) to analyze the structures below the PUK unconformity from two wells drilled recently in the North Gialo field (a mature reservoir). In addition, borehole images introduce new evidences that the PUK unconformity is angular and the bedding planes within the Nubian formation (below PUK) are significantly titled. Structural dips extracted from high resolution borehole images are used to construct a new geological model by the utilization of latest software technology. Therefore, it is important to use the advance well logs technology such as FMI-HD for any future drilling and up-date the existing model in order to minimize the structural uncertainty.

Keywords: FMI (formation micro imager), OBMI (oil base mud imager), UBI (ultra sonic borehole imager), nub sandstone reservoir in North gialo

Procedia PDF Downloads 317