Search results for: cut redundant information in image

Authors: Pratik Gandhi, Kavitha Chandra, Charles Thompson

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A computational model of the acoustic room impulse response between transmitters and receivers located in an enclosed cavity under the influence of frequency-dependent reflection coefficients of the walls is presented. The characteristic features of the impulse responses that differentiate these results from frequency-independent reflecting surfaces are discussed. The image-source model is derived from the first principle solution to Green's function of the acoustic wave equation. The post-processing of the computed impulse response with a band-pass filter to better represents the response of a loud-speaker is demonstrated.

Keywords: acoustic room impulse response, frequency dependent reflection coefficients, Green's function, image model

Procedia PDF Downloads 217

Authors: Tian Xia, Yuan Yan Tang

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In order to obtain higher small target detection accuracy, this paper presents an effective algorithm inspired by the local contrast mechanism. The proposed method can enhance target signal and suppress background clutter simultaneously. In the first stage, a enhanced image is obtained using the proposed Weighted Laplacian of Gaussian. In the second stage, an adaptive threshold is adopted to segment the target. Experimental results on two changeling image sequences show that the proposed method can detect the bright and dark targets simultaneously, and is not sensitive to sea-sky line of the infrared image. So it is fit for IR small infrared target detection.

Keywords: small target detection, local contrast, human vision system, Laplacian of Gaussian

Procedia PDF Downloads 453

Authors: Shu-Min Tsao, Chung-Ming Lo, Shao-Chun Chen

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Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient.

Keywords: computer-aided diagnosis, diabetic retinopathy, exudate, image processing

Procedia PDF Downloads 254

Authors: Suangsuda Subjaroen, Chutikarn Sriviboon, Rosjana Chandhasa

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This research aims to examine the graduates' overall satisfaction and influential factors that affect the image of Suan Sunandha Rajabhat University, according to the graduates' viewpoints on the graduation rehearsal day. In accordance with the graduates' perceptions, the study is related to the levels of graduates' satisfaction, their perceived quality, perceived value, and the image of Suan Sunandha Rajabhat University. The sample group in this study involved 1,129 graduates of Suan Sunandha Rajabhat University who attended on 2019 graduation rehearsal day. A questionnaire was used as an instrument in order to collect data. By the use of computing software, the statistics used for data analysis were various, ranging from frequencies, percentage, mean, and standard deviation, One-Way ANOVA, and Multiple Regression Analysis. The majority of participants were graduates with a bachelor's degree, followed by masters graduates and PhD graduates, respectively. Among the participants, most of them graduated from the Faculty of Management Sciences, followed by the Faculty of Humanities and Social Sciences and Faculty of Education, respectively. Overall, the graduates were satisfied with the graduation rehearsal day, and each aspect was rated at a satisfactory level. Formality, steps, and procedures were the aspects that graduates were most satisfied with, followed by graduation rehearsal personnel and staff, venue, and facilities. Referring to graduates' perceptions, the perceived quality was rated at a very good level, the perceived value was at a good level, whereas the image of Suan Sunandha Rajabhat University was perceived at a good level, respectively. There were differences in satisfaction levels among graduates with a bachelor's degree, graduates with a master's degree and a doctoral degree with statistical significance at the level of 0.05. There was a statistical significance at the level of 0.05 in perceived quality and perceived value affecting the image of Suan Sunandha Rajabhat University. The image of Suan Sunandha Rajabhat University influenced graduates' satisfaction level with statistical significance at the level of 0.01.

Keywords: university image, perceived quality, perceived value, intention to study higher education, intention to recommend the university to others

Procedia PDF Downloads 98

Authors: Thiago Brito Bezerra

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This paper presents a novel approach to reduce power consumption of digital filters based on dynamic bypassing of partial products in their multipliers. The bypassing elements incorporated into the multiplier hardware eliminate redundant signal transitions, which appear within the carry-save adders when the partial product is zero. This technique reduces the power consumption by around 20%. The circuit implementation was made using the AMS 0.18 um technology. The bypassing technique applied to the circuits is outlined.

Keywords: digital filter, low-power, bypassing technique, low-pass filter

Procedia PDF Downloads 366

Authors: R. Jannat, N. S. Juyena, F. Y. Bari, M. N. Islam

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Understanding anatomy of female reproductive organs is very much important to identify any variation in disease condition. Therefore, this study was conducted to determine the morphometry of female reproductive tract in small ruminant using ultrasonography. The reproductive tracts of 2l does and 20 ewes were collected, and both gross and ultrasonographic image measurements were performed to study morphometry of cervix, body of uterus, horn of uterus and ovary. Water bath ultrasonography technique was used with trans-abdominal linear probe for image measurements. Results revealed significant (P<0.001) variation among gross and image measurements of cervix, body of uterus and ovaries in does whereas, significant (P<0.001) variation existed between gross and image measurements of ovaries diameter in ewes. Gross measurements were proportionately higher than image measurements in both species. The mean length and width were found higher in right ovaries than those of left ovaries. In addition, the diameter of right ovaries was higher than those of left ovaries in both species. Pearson's correlation revealed a positive relation between two measurements. Moreover, it was found that echogenicity varied with reproductive organs. This is a model study. This study may help to identify female reproductive structures by trans-abdominal ultrasonography.

Keywords: female reproductive tract, morphometry, small ruminants, ultrasonography

Procedia PDF Downloads 260

Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

Procedia PDF Downloads 181

Authors: Sangeeta Yadav, Mantosh Biswas

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In this paper, we proposed an improved color based K-mean algorithm for clustering of satellite Image (SAR). Our method comprises of two stages. The first step is an interactive selection process where users are required to input the number of colors (ncolor), number of clusters, and then they are prompted to select the points in each color cluster. In the second step these points are given as input to K-mean clustering algorithm that clusters the image based on color and Minimum Square Euclidean distance. The proposed method reduces the mixed pixel problem to a great extent.

Keywords: cluster, ncolor method, K-mean method, interactive selection process

Procedia PDF Downloads 286

Authors: Tudor Barbu

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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

Procedia PDF Downloads 405

Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

Procedia PDF Downloads 144

Authors: Boukhatem Mohammed Belkaid, Lahdir Mourad

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In this paper, we propose a new encryption system for security issues meteorological images from Meteosat Second Generation (MSG), which generates 12 images every 15 minutes. The hybrid encryption scheme is based on AES and RSA algorithms to validate the three security services are authentication, integrity and confidentiality. Privacy is ensured by AES, authenticity is ensured by the RSA algorithm. Integrity is assured by the basic function of the correlation between adjacent pixels. Our system generates a unique password every 15 minutes that will be used to encrypt each frame of the MSG meteorological basis to strengthen and ensure his safety. Several metrics have been used for various tests of our analysis. For the integrity test, we noticed the efficiencies of our system and how the imprint cryptographic changes at reception if a change affects the image in the transmission channel.

Keywords: AES, RSA, integrity, confidentiality, authentication, satellite MSG, encryption, decryption, key, correlation

Procedia PDF Downloads 370

Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit

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In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.

Keywords: image processing technique, feature detections, surface registrations, capturing multi-view images, Production costs and Manufacturing processes

Procedia PDF Downloads 237

Authors: Li-Kai Kuo, Shyh-Hau Wang

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The kinetic trajectory of the median nerve (MN) in the wrist has shown to be capable of being applied to assess the carpal tunnel syndrome (CTS), and was found able to be detected by high-frequency ultrasound image via motion tracking technique. Yet, previous study may not quickly perform the measurement due to the use of a single element transducer for ultrasound image scanning. Therefore, previous system is not appropriate for being applied to clinical application. In the present study, B-mode ultrasound images of the wrist corresponding to movements of fingers from flexion to extension were acquired by clinical applicable real-time scanner. The kinetic trajectories of MN were off-line estimated utilizing two dimensional Baysian speckle tracking (TDBST) technique. The experiments were carried out from ten volunteers by ultrasound scanner at 12 MHz frequency. Results verified from phantom experiments have demonstrated that TDBST technique is able to detect the movement of MN based on signals of the past and present information and then to reduce the computational complications associated with the effect of such image quality as the resolution and contrast variations. Moreover, TDBST technique tended to be more accurate than that of the normalized cross correlation tracking (NCCT) technique used in previous study to detect movements of the MN in the wrist. In response to fingers’ flexion movement, the kinetic trajectory of the MN moved toward the ulnar-palmar direction, and then toward the radial-dorsal direction corresponding to the extensional movement. TDBST technique and the employed ultrasound image scanner have verified to be feasible to sensitively detect the kinetic trajectory and displacement of the MN. It thus could be further applied to diagnose CTS clinically and to improve the measurements to assess 3D trajectory of the MN.

Keywords: baysian speckle tracking, carpal tunnel syndrome, median nerve, motion tracking

Procedia PDF Downloads 483

Authors: R. Sumalatha, M. V. Subramanyam

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In medical image processing the quality of the image is degraded in the presence of noise. Especially in ultra sound imaging and Magnetic resonance imaging the data was corrupted by signal dependent noise known as salt and pepper noise. Removal of noise from the medical images is a critical issue for researchers. In this paper, a new type of technique Adaptive Spatial Mask Filter (ASMF) has been proposed. The proposed filter is used to increase the quality of MRI and ultra sound images. Experimental results show that the proposed filter outperforms the implementation of mean, median, adaptive median filters in terms of MSE and PSNR.

Keywords: salt and pepper noise, ASMF, PSNR, MSE

Procedia PDF Downloads 423

Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

Procedia PDF Downloads 125

Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

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In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach can overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, statistical moments, indexing, similarity distance, histograms intersection

Procedia PDF Downloads 442

Authors: Sameut Bouhaik Mostafa

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Information Act is the Canadian law gives the right of access to information for the institution of government. It declares the availability of government information to the public, but that exceptions should be limited and the necessary right of access to be specific, and also states the need to constantly re-examine the decisions on the disclosure of any government information independently from the government. By 1982, it enacted a dozen countries, including France, Denmark, Finland, Sweden, the Netherlands and the United States (1966) newly legally to access the information. It entered access to Canadian information into force of the Act of 1983, under the government of Pierre Trudeau, allowing Canadians to recover information from government files, and the development of what can be accessed from the information, and the imposition of timetables to respond. It has been applied by the Information Commissioner in Canada.

Keywords: law, information, management, legal

Procedia PDF Downloads 400

Authors: Javed Khan, Aamir Saeed Malik, Nidal Kamel, Sarat Chandra Dass, Azura Mohd Affandi

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Low contrast images can result from the wrong setting of image acquisition or poor illumination conditions. Such images may not be visually appealing and can be difficult for feature extraction. Contrast enhancement of color images can be useful in medical area for visual inspection. In this paper, a new technique is proposed to improve the contrast of color images. The RGB (red, green, blue) color image is transformed into normalized RGB color space. Adaptive histogram equalization technique is applied to each of the three channels of normalized RGB color space. The corresponding channels in the original image (low contrast) and that of contrast enhanced image with adaptive histogram equalization (AHE) are morphed together in proper proportions. The proposed technique is tested on seventy color images of acne patients. The results of the proposed technique are analyzed using cumulative variance and contrast improvement factor measures. The results are also compared with decorrelation stretch. Both subjective and quantitative analysis demonstrates that the proposed techniques outperform the other techniques.

Keywords: contrast enhacement, normalized RGB, adaptive histogram equalization, cumulative variance.

Procedia PDF Downloads 363

Authors: Zhuang Yiwen

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The paper examines the challenges facing the Singapore healthcare system related to the tracking and traceability of medical devices. One of the major challenges identified is the lack of a standard coding system for medical devices, which makes it difficult to track them effectively. The paper suggests the use of the Unique Device Identifier (UDI) as a single standard for medical devices to improve tracking and reduce errors. The paper also explores the use of barcoding and image recognition to identify and document medical devices in nursing practices. In nursing practices, the use of barcodes for identifying medical devices is common. However, the information contained in these barcodes is often inconsistent, making it challenging to identify which segment contains the model identifier. Moreover, the use of barcodes may be improved with the use of UDI, but many subsidized accessories may still lack barcodes. The paper suggests that the readiness for UDI and barcode standardization requires standardized information, fields, and logic in electronic medical record (EMR), operating theatre (OT), and billing systems, as well as barcode scanners that can read various formats and selectively parse barcode segments. Nursing workflow and data flow also need to be taken into account. The paper also explores the use of image recognition, specifically the Tesseract OCR engine, to identify and document implants in public hospitals due to limitations in barcode scanning. The study found that the solution requires an implant information database and checking output against the database. The solution also requires customization of the algorithm, cropping out objects affecting text recognition, and applying adjustments. The solution requires additional resources and costs for a mobile/hardware device, which may pose space constraints and require maintenance of sterile criteria. The integration with EMR is also necessary, and the solution require changes in the user's workflow. The paper suggests that the long-term use of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) as a supporting terminology to improve clinical documentation and data exchange in healthcare. SNOMED CT provides a standardized way of documenting and sharing clinical information with respect to procedure, patient and device documentation, which can facilitate interoperability and data exchange. In conclusion, the paper highlights the challenges facing the Singapore healthcare system related to the tracking and traceability of medical devices. The paper suggests the use of UDI and barcode standardization to improve tracking and reduce errors. It also explores the use of image recognition to identify and document medical devices in nursing practices. The paper emphasizes the importance of standardized information, fields, and logic in EMR, OT, and billing systems, as well as barcode scanners that can read various formats and selectively parse barcode segments. These recommendations could help the Singapore healthcare system to improve tracking and traceability of medical devices and ultimately enhance patient safety.

Keywords: medical device tracking, unique device identifier, barcoding and image recognition, systematized nomenclature of medicine clinical terms

Procedia PDF Downloads 64

Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

Procedia PDF Downloads 86

Authors: R. Kiran, B. R. Lakshmikantha, R. V. Parimala

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Secure operation of power systems requires monitoring of the system operating conditions. Phasor measurement units (PMU) are the device, which uses synchronized signals from the GPS satellites, and provide the phasors information of voltage and currents at a given substation. The optimal locations for the PMUs must be determined, in order to avoid redundant use of PMUs. The objective of this paper is to make system observable by using minimum number of PMUs & the implementation of stability software at 22OkV grid for on-line estimation of the power system transfer capability based on voltage and thermal limitations and for security monitoring. This software utilizes State Estimator (SE) and synchrophasor PMU data sets for determining the power system operational margin under normal and contingency conditions. This software improves security of transmission system by continuously monitoring operational margin expressed in MW or in bus voltage angles, and alarms the operator if the margin violates a pre-defined threshold.

Keywords: state estimator (SE), flexible ac transmission systems (FACTS), optimal location, phasor measurement units (PMU)

Procedia PDF Downloads 400

Authors: Li-Ting Huang, Yu-Hsiang Shen, Cing-Ciao Ke, Sheng-Pin Tseng, Fan-Pin Tseng, Yu-Ching Ni, Chia-Yu Lin

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Chest radiography is the most common technique for the diagnosis and follow-up of pulmonary diseases. However, the lesions superimposed with normal structures are difficult to be detected in chest radiography. Chest tomosynthesis is a relatively new technique to obtain 3D section images from a set of low-dose projections acquired over a limited angular range. However, there are some limitations with chest tomosynthesis. Patients undergoing tomosynthesis have to be able to hold their breath firmly for 10 seconds. A digital tomosynthesis system with advanced reconstruction algorithm and high-stability motion mechanism was developed by our research group. The potential for the system to perform a bidirectional chest scan within 10 seconds is expected. The purpose of this study is to realize the influences of the scan speed on the image quality for our digital tomosynthesis system. The major factors that lead image blurring are the motion of the X-ray source and the patient. For the fore one, an experiment of imaging a chest phantom with three different scan speeds, which are 6 cm/s, 8 cm/s, and 15 cm/s, was proceeded to understand the scan speed influences on the image quality. For the rear factor, a normal SD (Sprague-Dawley) rat was imaged with it alive and sacrificed to assess the impact on the image quality due to breath motion. In both experiments, the profile of the ROIs (region of interest) and the CNRs (contrast-to-noise ratio) of the ROIs to the normal tissue of the reconstructed images was examined to realize the degradations of the qualities of the images. The preliminary results show that no obvious degradation of the image quality was observed with increasing scan speed, possibly due to the advanced designs for the hardware and software of the system. It implies that higher speed (15 cm/s) than that of the commercialized tomosynthesis system (12 cm/s) for the proposed system is achieved, and therefore a complete chest scan within 10 seconds is expected.

Keywords: chest radiography, digital tomosynthesis, image quality, scan speed

Procedia PDF Downloads 320

Authors: Pallavi Mane, Nikita Mankar, Shraddha Mazire, Rasika Pashankar

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Content sharing sites are very useful in sharing information and images. However, with the increasing demand of content sharing sites privacy and security concern have also increased. There is need to develop a tool for controlling user access to their shared content. Therefore, we are developing an Adaptive Privacy Policy Prediction (A3P) system which is helpful for users to create privacy settings for their images. We propose the two-level framework which assigns the best available privacy policy for the users images according to users available histories on the site.

Keywords: online information services, prediction, security and protection, web based services

Procedia PDF Downloads 344

Authors: Abderrahim Elmoataz

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More and more contemporary applications involve data in the form of functions defined on irregular and topologically complicated domains (images, meshs, points clouds, networks, etc). Such data are not organized as familiar digital signals and images sampled on regular lattices. However, they can be conveniently represented as graphs where each vertex represents measured data and each edge represents a relationship (connectivity or certain affinities or interaction) between two vertices. Processing and analyzing these types of data is a major challenge for both image and machine learning communities. Hence, it is very important to transfer to graphs and networks many of the mathematical tools which were initially developed on usual Euclidean spaces and proven to be efficient for many inverse problems and applications dealing with usual image and signal domains. Historically, the main tools for the study of graphs or networks come from combinatorial and graph theory. In recent years there has been an increasing interest in the investigation of one of the major mathematical tools for signal and image analysis, which are Partial Differential Equations (PDEs) variational methods on graphs. The normalized p-laplacian operator has been recently introduced to model a stochastic game called tug-of-war-game with noise. Part interest of this class of operators arises from the fact that it includes, as particular case, the infinity Laplacian, the mean curvature operator and the traditionnal Laplacian operators which was extensiveley used to models and to solve problems in image processing. The purpose of this paper is to introduce and to study a new class of normalized p-Laplacian on graphs. The introduction is based on the extension of p-harmonious function introduced in as discrete approximation for both infinity Laplacian and p-Laplacian equations. Finally, we propose to use these operators as a framework for solving many inverse problems in image processing.

Keywords: normalized p-laplacian, image processing, stochastic game, inverse problems

Procedia PDF Downloads 497

Authors: Mananya Meenakorn

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The purpose of this research is to study the relationship customer perception and brand value of cosmetics in the view of customers in Thailand. The research is quantitative research using the survey method by questionnaire. Data were collected from female cosmetics consumer that residents in Bangkok, aged between 25-55 years. Researchers have determined the size of the sample by using Taro Yamane technic a total of 400 people. The study found the Shiseido cosmetics brand image always come with the new products innovation is in the height level. The average was 3.812, second is Shiseido brand has used innovation to produce the product for 3.792. And brand Shiseido looks luxury with an average of 3.707 respectively. In additional in terms of Lancôme cosmetic brand found the brand image is luxury at the height levels for 4.170 average. The seductive glamor is considered in the moderate with an average of 3.822 respectively.

Keywords: brand image, international fashion dress, values, working women

Procedia PDF Downloads 210

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

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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 555

Authors: Peiming Li

Abstract:

This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

Procedia PDF Downloads 48

Authors: Michael J. Hahn

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Docker is a powerful tool used by many companies such as PayPal, MetLife, Expedia, Visa, and many others. Docker works by bundling multiple applications, binaries, and libraries together on top of an operating system image called a container. The container runs on a Docker engine that in turn runs on top of a standard operating system. This centralization saves a lot of system resources. In this paper, we will be demonstrating how to bypass Transport Layer Security and execute remote code within Docker containers built on a base image of Alpine Linux version 3.7.0 through the use of .apk files due to flaws in the Alpine Linux package management program. This exploit renders any applications built using Docker with a base image of Alpine Linux vulnerable to unwanted outside forces.

Keywords: cloud, cryptography, Docker, Linux, security

Procedia PDF Downloads 184

Authors: Ayush Shrivastava, Arpit Chaudhary, Devang Kulshreshtha, Vibhav Prakash Singh, Rajeev Srivastava

Abstract:

Early diagnosis of breast cancer can improve the survival rate by detecting cancer at an early stage. Breast region segmentation is an essential step in the analysis of digital mammograms. Accurate image segmentation leads to better detection of cancer. It aims at separating out Region of Interest (ROI) from rest of the image. The procedure begins with removal of labels, annotations and tags from the mammographic image using morphological opening method. Pectoral Muscle Sliding Window Algorithm (PMSWA) is used for removal of pectoral muscle from mammograms which is necessary as the intensity values of pectoral muscles are similar to that of ROI which makes it difficult to separate out. After removing the pectoral muscle, Dispersed Region Growing Algorithm (DRGA) is used for segmentation of mammogram which disperses seeds in different regions instead of a single bright region. To demonstrate the validity of our segmentation method, 322 mammographic images from Mammographic Image Analysis Society (MIAS) database are used. The dataset contains medio-lateral oblique (MLO) view of mammograms. Experimental results on MIAS dataset show the effectiveness of our proposed method.

Keywords: CAD, dispersed region growing algorithm (DRGA), image segmentation, mammography, pectoral muscle sliding window algorithm (PMSWA)

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Authors: Devi Srinivas, K. Sindhuja

Abstract:

This paper presents architecture to improve surveillance applications based on the usage of the service oriented paradigm, with smart phones as user terminals, allowing application dynamic composition and increasing the flexibility of the system. According to the result of moving object detection research on video sequences, the movement of the people is tracked using video surveillance. The moving object is identified using the image subtraction method. The background image is subtracted from the foreground image, from that the moving object is derived. So the Background subtraction algorithm and the threshold value is calculated to find the moving image by using background subtraction algorithm the moving frame is identified. Then, by the threshold value the movement of the frame is identified and tracked. Hence, the movement of the object is identified accurately. This paper deals with low-cost intelligent mobile phone-based wireless video surveillance solution using moving object recognition technology. The proposed solution can be useful in various security systems and environmental surveillance. The fundamental rule of moving object detecting is given in the paper, then, a self-adaptive background representation that can update automatically and timely to adapt to the slow and slight changes of normal surroundings is detailed. While the subtraction of the present captured image and the background reaches a certain threshold, a moving object is measured to be in the current view, and the mobile phone will automatically notify the central control unit or the user through SMS (Short Message System). The main advantage of this system is when an unknown image is captured by the system it will alert the user automatically by sending an SMS to user’s mobile.

Keywords: security, graphical password, persuasive cued click points

Procedia PDF Downloads 524