Search results for: image matching technique
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9054

Search results for: image matching technique

8844 Model Order Reduction for Frequency Response and Effect of Order of Method for Matching Condition

Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

Abstract:

In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

Procedia PDF Downloads 371
8843 Conditions for Model Matching of Switched Asynchronous Sequential Machines with Output Feedback

Authors: Jung–Min Yang

Abstract:

Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the desired input/output behavior. A matrix expression is presented to address reachability of switched asynchronous sequential machines with output equivalence with respect to a model. The presented reachability condition for the controller design is validated in a simple example.

Keywords: asynchronous sequential machines, corrective control, model matching, input/output control

Procedia PDF Downloads 313
8842 Development of Algorithms for the Study of the Image in Digital Form for Satellite Applications: Extraction of a Road Network and Its Nodes

Authors: Zineb Nougrara

Abstract:

In this paper, we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We, therefore, have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.

Keywords: satellite image, road network, nodes, image analysis and processing

Procedia PDF Downloads 244
8841 Cross Matching: An Improved Method to Obtain Comprehensive and Consolidated Evidence

Authors: Tuula Heinonen, Wilhelm Gaus

Abstract:

At present safety, assessment starts with animal tests although their predictivity is often poor. Even after extended human use experimental data are often judged as the core information for risk assessment. However, the best opportunity to generate true evidence is to match all available information. Cross matching methodology combines the different fields of knowledge and types of data (e.g. in-vitro and in-vivo experiments, clinical observations, clinical and epidemiological studies, and daily life observations) and gives adequate weight to individual findings. To achieve a consolidated outcome, the information from all available sources is analysed and compared with each other. If single pieces of information fit together a clear picture becomes visible. If pieces of information are inconsistent or contradictory careful consideration is necessary. 'Cross' can be understood as 'orthographic' in geometry or as 'independent' in mathematics. Results coming from different sources bring independent and; therefore, they result in new information. Independent information gives a larger contribution to evidence than results coming repeatedly from the same source. A successful example of cross matching is the assessment of Ginkgo biloba where we were able to come to the conclusive result: Ginkgo biloba leave extract is well tolerated and safe for humans.

Keywords: cross-matching, human use, safety assessment, Ginkgo biloba leave extract

Procedia PDF Downloads 257
8840 Automatic Classification Using Dynamic Fuzzy C Means Algorithm and Mathematical Morphology: Application in 3D MRI Image

Authors: Abdelkhalek Bakkari

Abstract:

Image segmentation is a critical step in image processing and pattern recognition. In this paper, we proposed a new robust automatic image classification based on a dynamic fuzzy c-means algorithm and mathematical morphology. The proposed segmentation algorithm (DFCM_MM) has been applied to MR perfusion images. The obtained results show the validity and robustness of the proposed approach.

Keywords: segmentation, classification, dynamic, fuzzy c-means, MR image

Procedia PDF Downloads 443
8839 Detect Circles in Image: Using Statistical Image Analysis

Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee

Abstract:

The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.

Keywords: image processing, median filter, projection, scale-space, segmentation, threshold

Procedia PDF Downloads 401
8838 Adaptive Dehazing Using Fusion Strategy

Authors: M. Ramesh Kanthan, S. Naga Nandini Sujatha

Abstract:

The goal of haze removal algorithms is to enhance and recover details of scene from foggy image. In enhancement the proposed method focus into two main categories: (i) image enhancement based on Adaptive contrast Histogram equalization, and (ii) image edge strengthened Gradient model. Many circumstances accurate haze removal algorithms are needed. The de-fog feature works through a complex algorithm which first determines the fog destiny of the scene, then analyses the obscured image before applying contrast and sharpness adjustments to the video in real-time to produce image the fusion strategy is driven by the intrinsic properties of the original image and is highly dependent on the choice of the inputs and the weights. Then the output haze free image has reconstructed using fusion methodology. In order to increase the accuracy, interpolation method has used in the output reconstruction. A promising retrieval performance is achieved especially in particular examples.

Keywords: single image, fusion, dehazing, multi-scale fusion, per-pixel, weight map

Procedia PDF Downloads 440
8837 Digital Image Steganography with Multilayer Security

Authors: Amar Partap Singh Pharwaha, Balkrishan Jindal

Abstract:

In this paper, a new method is developed for hiding image in a digital image with multilayer security. In the proposed method, the secret image is encrypted in the first instance using a flexible matrix based symmetric key to add first layer of security. Then another layer of security is added to the secret data by encrypting the ciphered data using Pythagorean Theorem method. The ciphered data bits (4 bits) produced after double encryption are then embedded within digital image in the spatial domain using Least Significant Bits (LSBs) substitution. To improve the image quality of the stego-image, an improved form of pixel adjustment process is proposed. To evaluate the effectiveness of the proposed method, image quality metrics including Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), entropy, correlation, mean value and Universal Image Quality Index (UIQI) are measured. It has been found experimentally that the proposed method provides higher security as well as robustness. In fact, the results of this study are quite promising.

Keywords: Pythagorean theorem, pixel adjustment, ciphered data, image hiding, least significant bit, flexible matrix

Procedia PDF Downloads 311
8836 Mutual Information Based Image Registration of Satellite Images Using PSO-GA Hybrid Algorithm

Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

Abstract:

Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

Procedia PDF Downloads 376
8835 Design of a Graphical User Interface for Data Preprocessing and Image Segmentation Process in 2D MRI Images

Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

Abstract:

The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

Procedia PDF Downloads 348
8834 Image Enhancement of Histological Slides by Using Nonlinear Transfer Function

Authors: D. Suman, B. Nikitha, J. Sarvani, V. Archana

Abstract:

Histological slides provide clinical diagnostic information about the subjects from the ancient times. Even with the advent of high resolution imaging cameras the image tend to have some background noise which makes the analysis complex. A study of the histological slides is done by using a nonlinear transfer function based image enhancement method. The method processes the raw, color images acquired from the biological microscope, which, in general, is associated with background noise. The images usually appearing blurred does not convey the intended information. In this regard, an enhancement method is proposed and implemented on 50 histological slides of human tissue by using nonlinear transfer function method. The histological image is converted into HSV color image. The luminance value of the image is enhanced (V component) because change in the H and S components could change the color balance between HSV components. The HSV image is divided into smaller blocks for carrying out the dynamic range compression by using a linear transformation function. Each pixel in the block is enhanced based on the contrast of the center pixel and its neighborhood. After the processing the V component, the HSV image is transformed into a colour image. The study has shown improvement of the characteristics of the image so that the significant details of the histological images were improved.

Keywords: HSV space, histology, enhancement, image

Procedia PDF Downloads 306
8833 An Efficient Encryption Scheme Using DWT and Arnold Transforms

Authors: Ali Abdrhman M. Ukasha

Abstract:

Data security needed in data transmission, storage, and communication to ensure the security. The color image is decomposed into red, green, and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using a key image that has same original size and is generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours of color image recovery can be obtained with accepted level of distortion using Canny edge detector. Experiments have demonstrated that proposed algorithm can fully encrypt 2D color image and completely reconstructed without any distortion. It has shown that the color image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: color image, wavelet transform, edge detector, Arnold transform, lossy image encryption

Procedia PDF Downloads 451
8832 Application of the Hit or Miss Transform to Detect Dams Monitored for Water Quality Using Remote Sensing in South Africa

Authors: Brighton Chamunorwa

Abstract:

The current remote sensing of water quality procedures does not provide a step representing physical visualisation of the monitored dam. The application of the remote sensing of water quality techniques may benefit from use of mathematical morphology operators for shape identification. Given an input of dam outline, morphological operators such as the hit or miss transform identifies if the water body is present on input remotely sensed images. This study seeks to determine the accuracy of the hit or miss transform to identify dams monitored by the water resources authorities in South Africa on satellite images. To achieve this objective the study download a Landsat image acquired in winter and tested the capability of the hit or miss transform using shapefile boundaries of dams in the crocodile marico catchment. The results of the experiment show that it is possible to detect most dams on the Landsat image after the adjusting the erosion operator to detect pixel matching a percentage similarity of 80% and above. Successfully implementation of the current study contributes towards optimisation of mathematical morphology image operators. Additionally, the effort helps develop remote sensing of water quality monitoring with improved simulation of the conventional procedures.

Keywords: hit or miss transform, mathematical morphology, remote sensing, water quality monitoring

Procedia PDF Downloads 123
8831 External Retinal Prosthesis Image Processing System Used One-Cue Saliency Map Based on DSP

Authors: Yili Chen, Jixiang Fu, Zhihua Liu, Zhicheng Zhang, Rongmao Li, Nan Fu, Yaoqin Xie

Abstract:

Retinal prothesis is designed to help the blind to get some sight.It is made up of internal part and external part.In external part ,there is made up of camera, image processing, and RF transmitter.In internal part, there is RF receiver, implant chip,micro-electrode.The image got from the camera should be processed by suitable stragies to corresponds to stimulus the electrode.Nowadays, the number of the micro-electrode is hundreds and we don’t know the mechanism how the elctrode stimulus the optic nerve, an easy way to the hypothesis is that the pixel in the image is correspondence to the electrode.So it is a question how to get the important information of the image captured from the picture.There are many strategies to experimented to get the most important information as soon as possible, due to the real time system.ROI is a useful algorithem to extract the region of the interest.Our paper will explain the details of the orinciples and functions of the ROI.And based on this, we simplified the ROI algrithem,and used it in outside image prcessing DSP system of the retinal prothesis.Results show that our image processing stratiges is suitable for real-time retinal prothesis and can cut redundant information and help useful information to express in the low-size image.

Keywords: image processing, region of interest, saliency map, low-size image, useful information express, cut redundant information in image

Procedia PDF Downloads 253
8830 Image Segmentation Using 2-D Histogram in RGB Color Space in Digital Libraries

Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

Abstract:

This paper presents an unsupervised color image segmentation method. It is based on a hierarchical analysis of 2-D histogram in RGB color space. This histogram minimizes storage space of images and thus facilitates the operations between them. The improved segmentation approach shows a better identification of objects in a color image and, at the same time, the system is fast.

Keywords: image segmentation, hierarchical analysis, 2-D histogram, classification

Procedia PDF Downloads 353
8829 The Implementation of the Javanese Lettered-Manuscript Image Preprocessing Stage Model on the Batak Lettered-Manuscript Image

Authors: Anastasia Rita Widiarti, Agus Harjoko, Marsono, Sri Hartati

Abstract:

This paper presents the results of a study to test whether the Javanese character manuscript image preprocessing model that have been more widely applied, can also be applied to segment of the Batak characters manuscripts. The treatment process begins by converting the input image into a binary image. After the binary image is cleaned of noise, then the segmentation lines using projection profile is conducted. If unclear histogram projection is found, then the smoothing process before production indexes line segments is conducted. For each line image which has been produced, then the segmentation scripts in the line is applied, with regard of the connectivity between pixels which making up the letters that there is no characters are truncated. From the results of manuscript preprocessing system prototype testing, it is obtained the information about the system truth percentage value on pieces of Pustaka Batak Podani Ma AjiMamisinon manuscript ranged from 65% to 87.68% with a confidence level of 95%. The value indicates the truth percentage shown the initial processing model in Javanese characters manuscript image can be applied also to the image of the Batak characters manuscript.

Keywords: connected component, preprocessing, manuscript image, projection profiles

Procedia PDF Downloads 374
8828 Low-Cost Image Processing System for Evaluating Pavement Surface Distress

Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

Abstract:

Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

Procedia PDF Downloads 153
8827 Facial Biometric Privacy Using Visual Cryptography: A Fundamental Approach to Enhance the Security of Facial Biometric Data

Authors: Devika Tanna

Abstract:

'Biometrics' means 'life measurement' but the term is usually associated with the use of unique physiological characteristics to identify an individual. It is important to secure the privacy of digital face image that is stored in central database. To impart privacy to such biometric face images, first, the digital face image is split into two host face images such that, each of it gives no idea of existence of the original face image and, then each cover image is stored in two different databases geographically apart. When both the cover images are simultaneously available then only we can access that original image. This can be achieved by using the XM2VTS and IMM face database, an adaptive algorithm for spatial greyscale. The algorithm helps to select the appropriate host images which are most likely to be compatible with the secret image stored in the central database based on its geometry and appearance. The encryption is done using GEVCS which results in a reconstructed image identical to the original private image.

Keywords: adaptive algorithm, database, host images, privacy, visual cryptography

Procedia PDF Downloads 100
8826 A Hybrid Watermarking Model Based on Frequency of Occurrence

Authors: Hamza A. A. Al-Sewadi, Adnan H. M. Al-Helali, Samaa A. K. Khamis

Abstract:

Ownership proofs of multimedia such as text, image, audio or video files can be achieved by the burial of watermark is them. It is achieved by introducing modifications into these files that are imperceptible to the human senses but easily recoverable by a computer program. These modifications would be in the time domain or frequency domain or both. This paper presents a procedure for watermarking by mixing amplitude modulation with frequency transformation histogram; namely a specific value is used to modulate the intensity component Y of the YIQ components of the carrier image. This scheme is referred to as histogram embedding technique (HET). Results comparison with those of other techniques such as discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) have shown an enhance efficiency in terms of ease and performance. It has manifested a good degree of robustness against various environment effects such as resizing, rotation and different kinds of noise. This method would prove very useful technique for copyright protection and ownership judgment.

Keywords: authentication, copyright protection, information hiding, ownership, watermarking

Procedia PDF Downloads 543
8825 Robust Image Registration Based on an Adaptive Normalized Mutual Information Metric

Authors: Huda Algharib, Amal Algharib, Hanan Algharib, Ali Mohammad Alqudah

Abstract:

Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy.

Keywords: image registration, mutual information, image gradients, image transformations

Procedia PDF Downloads 217
8824 Automatic Target Recognition in SAR Images Based on Sparse Representation Technique

Authors: Ahmet Karagoz, Irfan Karagoz

Abstract:

Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

Procedia PDF Downloads 340
8823 TACTICAL: Ram Image Retrieval in Linux Using Protected Mode Architecture’s Paging Technique

Authors: Sedat Aktas, Egemen Ulusoy, Remzi Yildirim

Abstract:

This article explains how to get a ram image from a computer with a Linux operating system and what steps should be followed while getting it. What we mean by taking a ram image is the process of dumping the physical memory instantly and writing it to a file. This process can be likened to taking a picture of everything in the computer’s memory at that moment. This process is very important for tools that analyze ram images. Volatility can be given as an example because before these tools can analyze ram, images must be taken. These tools are used extensively in the forensic world. Forensic, on the other hand, is a set of processes for digitally examining the information on any computer or server on behalf of official authorities. In this article, the protected mode architecture in the Linux operating system is examined, and the way to save the image sample of the kernel driver and system memory to disk is followed. Tables and access methods to be used in the operating system are examined based on the basic architecture of the operating system, and the most appropriate methods and application methods are transferred to the article. Since there is no article directly related to this study on Linux in the literature, it is aimed to contribute to the literature with this study on obtaining ram images. LIME can be mentioned as a similar tool, but there is no explanation about the memory dumping method of this tool. Considering the frequency of use of these tools, the contribution of the study in the field of forensic medicine has been the main motivation of the study due to the intense studies on ram image in the field of forensics.

Keywords: linux, paging, addressing, ram-image, memory dumping, kernel modules, forensic

Procedia PDF Downloads 79
8822 Frequency of Occurrence Hybrid Watermarking Scheme

Authors: Hamza A. Ali, Adnan H. M. Al-Helali

Abstract:

Generally, a watermark is information that identifies the ownership of multimedia (text, image, audio or video files). It is achieved by introducing modifications into these files that are imperceptible to the human senses but easily recoverable by a computer program. These modifications are done according to a secret key in a descriptive model that would be either in the time domain or frequency domain or both. This paper presents a procedure for watermarking by mixing amplitude modulation with frequency transformation histogram; namely a specific value is used to modulate the intensity component Y of the YIQ components of the carrier image. This scheme is referred to as histogram embedding technique (HET). Results comparison with those of other techniques such as discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) have shown an enhance efficiency in terms of ease and performance. It has manifested a good degree of robustness against various environment effects such as resizing, rotation and different kinds of noise. This method would prove very useful technique for copyright protection and ownership judgment.

Keywords: watermarking, ownership, copyright protection, steganography, information hiding, authentication

Procedia PDF Downloads 348
8821 Color Image Enhancement Using Multiscale Retinex and Image Fusion Techniques

Authors: Chang-Hsing Lee, Cheng-Chang Lien, Chin-Chuan Han

Abstract:

In this paper, an edge-strength guided multiscale retinex (EGMSR) approach will be proposed for color image contrast enhancement. In EGMSR, the pixel-dependent weight associated with each pixel in the single scale retinex output image is computed according to the edge strength around this pixel in order to prevent from over-enhancing the noises contained in the smooth dark/bright regions. Further, by fusing together the enhanced results of EGMSR and adaptive multiscale retinex (AMSR), we can get a natural fused image having high contrast and proper tonal rendition. Experimental results on several low-contrast images have shown that our proposed approach can produce natural and appealing enhanced images.

Keywords: image enhancement, multiscale retinex, image fusion, EGMSR

Procedia PDF Downloads 430
8820 Examination of 12-14 Years Old Volleyball Players’ Body Image Levels

Authors: Dilek Yalız Solmaz, Gülsün Güven

Abstract:

The aim of this study is to examine the body image levels of 12-14 years old girls who are playing volleyball. The research group consists of 113 girls who are playing volleyball in Sakarya during the fall season of 2015-2016. Data was collected by means of the 'Body Image Questionnaire' which was originally developed by Secord and Jourard. The consequence of repeated analysis of the reliability of the scale was determined to as '.96'. This study employed statistical calculations as mean, standard deviation and t-test. According to results of this study, it was determined that the mean point of the volleyball players is 158.5 ± 25.1 (minimum=40; maximum=200) and it can be said that the volleyball players’ body image levels are high. There is a significant difference between the underweight (167.4 ± 20.7) and normal weight (151.4 ± 26.2) groups according to their Body Mass Index. Body image levels of underweight group were determined higher than normal weight group.

Keywords: volleyball, players, body image, body image levels

Procedia PDF Downloads 185
8819 Determining Water Quantity from Sprayer Nozzle Using Particle Image Velocimetry (PIV) and Image Processing Techniques

Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

Abstract:

Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

Procedia PDF Downloads 211
8818 The Amount of Conformity of Persian Subject Headlines with Users' Social Tagging

Authors: Amir Reza Asnafi, Masoumeh Kazemizadeh, Najmeh Salemi

Abstract:

Due to the diversity of information resources in the web0.2 environment, which is increasing in number from time to time, the social tagging system should be used to discuss Internet resources. Studying the relevance of social tags to thematic headings can help enrich resources and make them more accessible to resources. The present research is of applied-theoretical type and research method of content analysis. In this study, using the listing method and content analysis, the level of accurate, approximate, relative, and non-conformity of social labels of books available in the field of information science and bibliography of Kitabrah website with Persian subject headings was determined. The exact matching of subject headings with social tags averaged 22 items, the approximate matching of subject headings with social tags averaged 36 items, the relative matching of thematic headings with social tags averaged 36 social items, and the average matching titles did not match the title. The average is 116. According to the findings, the exact matching of subject headings with social labels is the lowest and the most inconsistent. This study showed that the average non-compliance of subject headings with social labels is even higher than the sum of the three types of exact, relative, and approximate matching. As a result, the relevance of thematic titles to social labels is low. Due to the fact that the subject headings are in the form of static text and users are not allowed to interact and insert new selected words and topics, and on the other hand, in websites based on Web 2 and based on the social classification system, this possibility is available for users. An important point of the present study and the studies that have matched the syntactic and semantic matching of social labels with thematic headings is that the degree of conformity of thematic headings with social labels is low. Therefore, these two methods can complement each other and create a hybrid cataloging that includes subject headings and social tags. The low level of conformity of thematic headings with social tags confirms the results of backgrounds and writings that have compared the social tags of books with the thematic headings of the Library of Congress. It is not enough to match social labels with thematic headings. It can be said that these two methods can be complementary.

Keywords: Web 2/0, social tags, subject headings, hybrid cataloging

Procedia PDF Downloads 135
8817 Iris Recognition Based on the Low Order Norms of Gradient Components

Authors: Iman A. Saad, Loay E. George

Abstract:

Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

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8816 Review on Effective Texture Classification Techniques

Authors: Sujata S. Kulkarni

Abstract:

Effective and efficient texture feature extraction and classification is an important problem in image understanding and recognition. This paper gives a review on effective texture classification method. The objective of the problem of texture representation is to reduce the amount of raw data presented by the image, while preserving the information needed for the task. Texture analysis is important in many applications of computer image analysis for classification include industrial and biomedical surface inspection, for example for defects and disease, ground classification of satellite or aerial imagery and content-based access to image databases.

Keywords: compressed sensing, feature extraction, image classification, texture analysis

Procedia PDF Downloads 401
8815 Image Segmentation Using Active Contours Based on Anisotropic Diffusion

Authors: Shafiullah Soomro

Abstract:

Active contour is one of the image segmentation techniques and its goal is to capture required object boundaries within an image. In this paper, we propose a novel image segmentation method by using an active contour method based on anisotropic diffusion feature enhancement technique. The traditional active contour methods use only pixel information to perform segmentation, which produces inaccurate results when an image has some noise or complex background. We use Perona and Malik diffusion scheme for feature enhancement, which sharpens the object boundaries and blurs the background variations. Our main contribution is the formulation of a new SPF (signed pressure force) function, which uses global intensity information across the regions. By minimizing an energy function using partial differential framework the proposed method captures semantically meaningful boundaries instead of catching uninterested regions. Finally, we use a Gaussian kernel which eliminates the problem of reinitialization in level set function. We use several synthetic and real images from different modalities to validate the performance of the proposed method. In the experimental section, we have found the proposed method performance is better qualitatively and quantitatively and yield results with higher accuracy compared to other state-of-the-art methods.

Keywords: active contours, anisotropic diffusion, level-set, partial differential equations

Procedia PDF Downloads 143