International Journal of Image, Graphics and Signal Processing @ijigsp
Статьи журнала - International Journal of Image, Graphics and Signal Processing
Все статьи: 1110
Indian Sign Language Recognition Using 2-D Convolution Neural Network and Graphical User Interface
Статья научная
The emergence of the sign Language recollection method has a great effect on the day-to-day livings of human beings with hearing disabled individuals utilizing signs to speak with others. Much the same as verbally communicated in dialects, there is no general language as each nation has its communication in language, so every nation has its vernacular of gesture-based communication and in India, they utilize Indian Sign Language (ISL). Over the most recent couple of years, analysts have investigated the computerization of ISL. Here we developed the custom database for 26 English letters and each Letter narrates the 5 times by each person. Train the dataset using 2D CNN and create GUI for recognition. A few endeavors have been made in India and different nations. We attempt to investigate and dissect the ISL that has been made with the mechanization of communication through signing and motion acknowledgment. We attempted to investigate the difficulties that come in the ongoing sign acknowledgment framework. The testing accuracy of the proposed work is 95% and 95% for the validation accuracy.
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Influence of Metal Pipes in the Environment on Designing the Underground Electrical Installations
Статья научная
Underground installations are networks of metal pipes and cables in space at a certain distance from the ground surface. Insulating layers of metal pipes of underground installations (gas, plumbing, electrical...) do not provide their full protection against corrosion and breakdowns. In urban areas, wandering currents (electric rail or earthing of power plants) repeatedly increase failures in underground installations in the environment. That is why a certain kind of protection is foreseen for the protection of metal pipes of underground installations against corrosion and destruction from wandering currents. However, until today there is no universal method for calculating the parameters of stationary and quasi-stationary electric fields of wandering currents and a general solution for arbitrary configuration, but it is possible to form a model algorithm for controlling the state and failures of insulation of underground electrical installations. Solutions for wandering currents could be determined by the criterion of similarity to transient currents on power lines. In the paper, in program MATLAB Simulink a simulation for the correction of wandering currents using foreign grounding has been performed on certain parts of underground installations. It has been shown that the solution of the task is possible with help of the model-algorythm which allows a determinaitn of the power on isolation layer of the cable sheat, and with simulation of the different versions of schedule of protective equipment, their optimal schedule could be determined.
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Статья научная
At the current moment, all developed polarization methods utilize "single-point" statistical analysis algorithms for laser fields. A relevant task is to generalize traditional techniques by incorporating new correlation-based "two-point" algorithms for the analysis of polarization images. Theoretical foundations of the mutual and autocorrelation processing of phase maps of polarization-structural images of samples of dehydrated serum films are given. The maps of a new polarization-correlation parameters, namely complex degree of coherence (CDC) and complex degree of mutual polarization (CDMP) of soft matter layer boundary field by the example of dehydrated serum film samples are investigated. Two groups of representative samples, uterine myoma patients (control group 1) and patients with external genital endometriosis (study group 2), were considered. We applied a complex algorithm of analytical data processing - statistical (1stand 4th central statistical moments), correlation (Gram-Charlie expansion coefficients of autocorrelation functions) and fractal (fractal dimensions) parameters of polarization-correlation parameters maps. Objective markers for diagnosing extragenital endometriosis were found.
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Infrared and Microwave Image Fusion for Rainfall Detection over Northern Algeria
Статья научная
Rain areas delineation proposed in this paper is based on the image fusion from geostationary Meteosat Second Generation (MSG) satellite, with the low-earth orbiting passive Tropical Rainfall Measuring Mission (TRMM) satellite. The fusion technique described in this work used an artificial neural network (ANN). It's has been developed to detect instantaneous rainfall by using information from the IR images of MSG satellite and from TRMM Microwave Imager (TMI). The study is carried out over north of Algeria. Seven spectral parameters are used as input data of ANN to identify raining or non - raining pixels. Corresponding data of raining /non-raining pixels are taken from a PR (precipitation radar) issued from TRMM. Results from the developed scheme are compared with the results of SI method (Scattering Index) taken as reference method. The results show that the developed model performs very well and overcomes the deficiencies of use a single satellite.
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Статья научная
The combination of visible and infrared images from different sensors can provide a more detailed and informative image. Visible images capture environmental details and texture, while infrared sensors can detect thermal radiation and create grayscale images that have high contrast. These images are useful for distinguishing between target and background in challenging conditions, such as at night or in inclement weather. When these two types of images are fused, they create high- contrast images with rich texture and target details. In this paper, an effective image fusion technique has been developed, which utilizes Latent Low Rank Representation (LatLRR) method that decomposes the source images into latent low rank and salient parts to capture common and unique information respectively. The proposed network design incorporates the dense network and VGG-19 architectures for deep feature extraction of latent low- rank and salient parts, that minimize distortion while maintaining crucial texture and details in the output. Weighted average fusion strategies are used to combine these latent low-rank and salient parts, and the resulting fused features are used for feature reconstruction to generate a fused low-rank and salient part. These parts are integrated to yield a fused image output. The proposed approach out performs existing state-of-the-art methods on both visual characteristics and objective evaluation metrics.
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Статья научная
Image Inpainting of ruined historic monuments and heritage sites can help in visualizing how these may have existed in the past. An inpainted image of a monument can serve as a tool for physical reconstruction purpose. The purpose of the proposed method is to fill cracks and gaps of selected damaged regions in heritage monuments by exploiting the statistical properties of foreground and background along with the spatial location of the damage in the image of the monuments. The patch based image inpainting algorithm is improved by segmenting the image using K means clustering to search the candidate patches in relevant source region only. Segmentation improves patch searching in terms of both quality and time. The priority of the patch to fill is decided based on the standard deviation of the patch around destination pixel. Kn similar patches are selected from the source region based on minimum value of sum squared distance. The selected patches are refined using an efficient patch refinement scheme using higher order singular value decomposition to capture underlying pattern among the candidate source patches. The threshold for refinement is selected by using minimum and maximum value of standard deviation of the target patch. This eliminates random variation and unwanted artifacts. Experimental results carried on a large number of natural images and comparisons with well-known existing methods demonstrate the efficacy and superiority of the proposed method.
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Integrated Gabor Filter and Trilateral Filter for Exudate Extraction in Fundus Images
Статья научная
Image segmentation is the process of dividing an electronic digital image into numerous sub-images. Its objective is to categorize image into various regions in such a way that every potential object in image gets individual sector. Instinctive recognition of diabetic retinopathy wounds, like exudates can provide opportunity to identify certain diseases. Lack of accuracy in these techniques can lead to fatal results because of incorrect treatment. So, there is a great need for automation techniques with high accuracy for retinal disease identification. Several automation techniques have been proposed for retinal image analysis which can detect the exudates in fundus images in more promising manner. The related work has found that the issue of noise in fundus images is ignored in the majority of existing literature. Although Gabor filter bank has shown significant results over available techniques, but it is poor in its speed. Also it is not very efficient for multiple kinds of noises at a same time. Therefore to improve the accuracy of exudate extraction further a Hybrid Gabor filter bank with trilateral based filtering technique is proposed. This filtering will use improved trilateral filtering which enables us to detect exudates even in highly corrupted noisy images.
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Integrating Occlusion and Illumination Modeling for Object Tracking Using Image Annotation
Статья научная
Tracking occluded objects at different depths has become as extremely important component of study for any video sequence having wide applications in object tracking, scene recognition, coding, editing the videos and mosaicking. This paper experiments with the capabilities of image annotation contour based tracking for occluded object. Image annotation is applied on 3 similar normal video sequences varying in depth. In the experiment, one bike occludes the other at a depth of 60 cm, 80 cm and 100 cm respectively. The effect on tracking is also analyzed with illumination variations using 3 different light sources in video sequences having objects occluding one another at same depth. The paper finally studies the ability of annotation to track the occluded object based on pyramids with variation in depth further establishing a threshold at which the ability of the system to track the occluded object fails. The contour of both the individual objects can’t be tracked due to the distortion caused by overlapping of the object pyramids. The thresholds established can be used as a bench mark to estimate the capability of different softwares. The paper further computes the frame by frame error incurred by the system, supported by detailed simulations. This system can be effectively used to achieve flawless tracking as the error in motion tracking can be corrected. This can be of great interest to computer scientists while designing surveillance systems etc.
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Статья научная
Image segmentation generally refers to the process that partitions an image into mutually exclusive regions that cover the image. Among the various image segmentation techniques, traditional image segmentation methods like edge detection, region based, watershed transformation etc. are widely used but have certain drawbacks, which cannot be used for the accurate result. In this paper clustering based techniques is employed on images which results into segmentation of images. The performance of Fuzzy C-means (FCM) integrated with the Particle Swarm optimization (PSO) technique and its variations are analyzed in different application fields. To analyze and grade the performance, computational and time complexity of techniques in different fields several metrics are used namely global consistency error, probabilistic rand index and variation of information are used. This experimental performance analysis shows that FCM along with fractional order Darwinian PSO give better performance in terms of classification accuracy, as compared to other variation of other techniques used. The integrated algorithm tested on images proves to give better results visually as well as objectively. Finally, it is concluded that fractional order Darwinian PSO along with neighborhood Fuzzy C-means and partial differential equation based level set method is an effective image segmentation technique to study the intricate contours provided the time complexity should be as small as possible to make it more real time compatible.
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Intelligent Geometric Classification of Irregular Patterns via Probabilistic Neural Network
Статья научная
This paper deals with interpretation of patterns via neural networks under organization and classification approaches. Fifty different groups of images including geometric shapes, mechanical instruments, machines, animals, fruits, and other classes of samples are classified here in two successive steps. Each primary category is divided into three different sub-groups. The purpose is identifying the class and sub-class of each input sample. Nowadays, industry and manufacturing are moving towards automation; hence accurate description of photos results in a myriad of industrial, security, and medical applications and takes a pressing part in artificial intelligence's progression. Intelligent interpretation of structure's design in CNC machine eventuates in autonomous selection of cutting tools by which any structure can easily be manufactured. Anyhow, this paper comes up with a pattern interpretation method to be applied in submarine detection purposes. Remotely operated vehicles (ROV) are used to detect and survey oil pipelines and underwater marine structures, so mentioned neural network classification is a practicable tool for detection mechanism and avoiding obstacles in ROVs.
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Intelligent Infective Endocarditis Diagnostic System Based on Echocardiography
Статья научная
In this paper, we developed a new approach to solve the problem of infective endocarditis (IE) diagnostics based on intelligent analysis of patients’ echocardiography images. The approach is based on echocardiography segmentation results and detection of valvular anomalies (namely vegetations). In this article for the first time investigates CNNs and Visual Transformers (ViT) based segmentation methods within the framework of the vegetation segmentation task on echocardiography images. Additionally, ensemble methods for combining segmentation models using a new method of models competition for data points were proposed. Furthermore, we investigated methods for aggregating the results of the ensemble based on a new meta-model, pointwise weighted aggregation, which weighs the results of each model pixel by pixel. The last proposed step was to automatically calculate the volume of segmented vegetation to determine the degree of disease and the need for urgent surgical intervention. For the studied and proposed methods, the following ensemble segmentation accuracy was achieved on the test dataset: iou 0.7822, dice score 0.886. The proposed empirical algorithm for calculating the volume of vegetations provided the basis for further improvements of the studied approach. The results obtained indicate the great potential of the developed approaches in clinical practice.
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Статья научная
This project aims to enhance online experiences quality by giving users greater control over the content they encounter daily. The proposed solution is particularly valuable for parents seeking to safeguard their children, educational institutions striving to foster a more conducive learning environment, and individuals prioritising ethical internet usage. It also supports users who wish to limit their exposure to misinformation, including fake news, propaganda, and disinformation. Through the implementation of a browser extension, this system will contribute to a safer internet, reducing users' vulnerability to harmful content and promoting a more positive and productive online environment. The primary objective of this work is to develop a browser extension that automatically detects and censors inappropriate text and images on web pages using artificial intelligence (AI) technologies. The extension will enable users to personalise censorship settings, including the ability to define custom prohibited words and toggle the filtering of text and images. Accuracy estimates for various classifiers such as Random Forest (0.879), Logistic Regression (0.904), Decision Tree (0.878), Naive Bayes (0.315), and KNN (0.832) were performed.
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Interfacing the Analog Camera with FPGA Board for Real-time Video Acquisition
Статья научная
Advances in FPGA technology have dramatically increased the use of FPGAs for computer vision applications. The primary task for development of such FPGAs based systems is the interfacing of the analog camera with FPGA board. This paper describes the design and implementation of camera interface module required for connecting analog camera with Xilinx ML510 (Virtex–5 FXT) FPGA board having no video input port. Digilent VDEC1 video daughter card is used for digitizing the analog video into digital form. The necessary control logics for video acquisition and video display are designed using VHDL and Verilog, simulated in ModelSim, and synthesized using Xilinx ISE 12.1. Designed and implemented interfaces provide the real-time video acquisition and display.
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Статья научная
The subject of the research in this scientific paper is the text on the Web pages, with special emphasis on the interpretation of the text fonts chosen by the Web designer, along with its typographic features, on computers of various users. In addition, users can have different operating systems, different browsers, and different preferences in terms of their computers settings. An overall direction of the choice of fonts and their characteristics when designing Web pages, as well as some advice and opinions on the same topic are presented here. After that, several problems which arise from the interpretation of the text on the Web pages of the users are analyzed, for which a few solutions for the problems, as well as recommendations on which solution when to be chosen are also given in this text. The problem of having no fonts, chosen by the designer, on the user's computer is studied as well. Then, the possibility of the users to change the default font, given by the designer, on their computers, and the possibility to change the typographic features of the default font is also analyzed. Finally, the problem with incompatibility with different operating systems and Web browsers in visualizing the fonts is also considered.
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Intravascular Ultrasound Image Segmentation Using Morphological Snakes
Статья научная
From the first use of the technics of intravascular ultrasound (IVUS) as an imaging technique for the coronary artery system at the 70th century until now , the segmentation of the arterial wall boundaries still an important problem . Much research has been done to give better segmentation result for better diagnostics , evaluation and therapy planning. In this paper we present a new segmentation technics based on Morphological Snakes which developed by Luis Álvarez used for the first time for IVUS segmentation. It is a simple , fast and stable approach of snakes evolution algorithm. Results are presented and discussed in order to demonstrate the effectiveness of this approach in IVUS segmentation.
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Статья научная
Concrete crane beam on a rock wall on a new structure used in underground building has become more common in recent year. But the concrete beam cracking problem always perplexes scientists and engineers. In order to solve this, the construction information inversion and feedback analysis method is applied. A beam section was taken as a prototype experiment. The temperature and construction data was collected to inverse some necessary thermal parameters. According to the characteristics of concrete temperature field, the basic accelerating genetic algorithm was improved. The improved accelerating genetic algorithm has the merits of high precision and fast calculation. With this algorithm, the calculation temperature and measured value are very close, which shows the method is efficiency. Then inversed parameters were applied in the feedback simulation. According to the simulation results, the proper temperature control method was suggested. By this way, the concrete temperature was controlled well and the beams appear no crack in recent two year. The successful application shows that the inversion and feedback analysis of concrete temperature field can reflect the factual performance of concrete and give important direction to engineering construction.
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Investigation of Wavelets for Representation and Compression of Skin Cancer Images
Статья научная
Wavelets play a key role in many applications like image representations and compression, which is a main issue in the process of reducing the size in bytes of a digital image file to store it in the memory and as well as to transmit. This paper presents image representation using various wavelet transforms. In the proposed method, the comparison between wavelets applied on an image are considered by counting the number of approximation coefficients retained for the representation of images and comparative analysis of the standard wavelets available is presented. This paper mainly aims at the type of the wavelet which retains less number of approximation coefficients for representing skin cancer image and gives the reduced compressed file size by considering the various parameters like Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity Index Measure (SSIM) and Compression Efficiency.
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Iris Biometric Authentication used for Security Systems
Статья научная
Pupil detection and iris localisation using scanning method and feature extraction is performed with five level decomposition techniques, with these two proposed algorithm we could achieve efficient and fast person authentication in biometric security systems. Statistical performance evaluation is also performed using parameters False acceptance rate (FAR), False rejection rate (FRR), Correct recognition rate (CRR), Equal error rate (EER), Match ratio etc, using CASIA database.
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Статья научная
Classification task on the human facial attribute is hard because of the similarities in between classes. For example, emotion classification and age estimation are two important applications. There are very little changes between the different emotions of a person and a different person has a different way of expressing the same emotion. Same for age classification. There is little difference between consecutive ages. Another problem is the image resolution. Small images contain less information and large image requires a large model and lots of data to train properly. To solve both of these problems this work proposes using transfer learning on a pre-trained model combining a custom loss function called Island Loss to reduce the intra-class variation and increase the inter-class variation. The experiments have shown impressive results on both of the application with this method and achieved higher accuracies compared to previous methods on several benchmark datasets.
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JPEG Image Steganography based on Coefficients Selection and Partition
Статья научная
In this paper, we propose a novel JPEG image Steganography algorithm based on partition schemes on image coefficient values. Our method selects the AC and DC coefficients of a JPEG image according to a channel selection method and then identifies appropriate coefficients to store the secret data-bits. As opposed to other reported works, in our algorithm each selected coefficient can store a variable number of data-bits that are decided using the concept called ‘Partition Scheme’. Experimental results indicate the suitability of the proposed algorithm as compared to other existing methods.
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