This paper presents a study on the exploitation of visual information from two points of view radically different. Computer vision is a branch of artificial intelligence that focuses on the extraction of useful inform...
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ISBN:
(纸本)9781509016457
This paper presents a study on the exploitation of visual information from two points of view radically different. Computer vision is a branch of artificial intelligence that focuses on the extraction of useful information in an image. image matching is a fundamental aspect of many problems in computer vision. Several algorithms have been developed for this purpose. Based on this research, this paper present all the previous work reviewed.
Rail transportation systems, which are commonly used in today's world, should be inspected at certain intervals for possible accidents. During the rail inspection, the physical vibration on rail lines causes a blu...
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ISBN:
(纸本)9781467395557
Rail transportation systems, which are commonly used in today's world, should be inspected at certain intervals for possible accidents. During the rail inspection, the physical vibration on rail lines causes a blurring effect on the images. Doing deblurring automatically requires information of blurring rates and specifying the parameters accordingly for deblurring. With this purpose, a test equipment which can move on rail lines and a camera system for the detection of blurring and deblurring is integrated with Inertial Measurement Unit (EMU) is promoted in this study. Then, with Attitude and Heading Reference System (AHRS) algorithm, the effect of blurring at the moment of the vibration is examined, point spread function (PSF) value is chosen dynamically and deblurring is achieved. In order to increase the accuracy rates of detection algorithms, a pretreatment method is proposed for detecting the blur effect and removing it.
Evolutionary algorithms are metaheuristic algorithms that mimic biological mechanisms for the solution of optimization problems. They are widely used in many problems of engineering, including image analysis and patte...
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ISBN:
(纸本)9781509018178
Evolutionary algorithms are metaheuristic algorithms that mimic biological mechanisms for the solution of optimization problems. They are widely used in many problems of engineering, including image analysis and pattern recognition. Such methods had shown added value in overcoming certain problems and limitiations of more traditional methods and approaches. This is particularlay interesting in Computer for designing faster and more accurate optimization methods. Despite recent advances in image registration, there is still room for improvement especially with the use of metaheuristic algorithms. In this paper, we present a novel method for solving the automated rigid registration problem by introducing a variant of the relatively new metaheuristic method called harmony search which shows promising results in difficult rigid registration cases.
This paper proposed an algorithm that detects traffic light colors for colorblind individuals, the proposed algorithm employs imageprocessing techniques associated in imageprocessing toolbox in LabVIEW to help color...
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This paper proposed an algorithm that detects traffic light colors for colorblind individuals, the proposed algorithm employs imageprocessing techniques associated in imageprocessing toolbox in LabVIEW to help colorblind individuals in identifying the colors of traffic lights. It uses a fixed mobile camera to capture traffic light images taken in different roads and streets in Jordan and Kuwait. It detects traffic lights by comparing the candidate traffic light with some in-house collected traffic light templates, comparison is based on correlation. The templates represent 22 different shapes of traffic lights in Jordan and Kuwait. Finally, the algorithm extracts the green and the red planes and recognizes their colors. Experimental results reveal the accuracy of proposed algorithm in identifying the colors of traffic lights in different cases and circumstances. Hence, our proposed algorithm is helpful for colorblind drivers.
Computational photography systems are becoming increasingly diverse, while computational resources-for example on mobile platforms-are rapidly increasing. As diverse as these camera systems may be, slightly different ...
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Computational photography systems are becoming increasingly diverse, while computational resources-for example on mobile platforms-are rapidly increasing. As diverse as these camera systems may be, slightly different variants of the underlying imageprocessing tasks, such as demosaicking, deconvolution, denoising, inpainting, image fusion, and alignment, are shared between all of these systems. Formal optimization methods have recently been demonstrated to achieve state-of-the-art quality for many of these applications. Unfortunately, different combinations of natural image priors and optimization algorithms may be optimal for different problems, and implementing and testing each combination is currently a time-consuming and error-prone process. ProxImaL is a domain-specific language and compiler for image optimization problems that makes it easy to experiment with different problem formulations and algorithm choices. The language uses proximal operators as the fundamental building blocks of a variety of linear and nonlinear image formation models and cost functions, advanced image priors, and noise models. The compiler intelligently chooses the best way to translate a problem formulation and choice of optimization algorithm into an efficient solver implementation. In applications to the imageprocessing pipeline, deconvolution in the presence of Poisson-distributed shot noise, and burst denoising, we show that a few lines of ProxImaL code can generate highly efficient solvers that achieve state-of-the-art results. We also show applications to the nonlinear and nonconvex problem of phase retrieval.
Automatic traffic sign detection and recognition (TSDR) is one of the most significant areas of object detection. In spite of numerous researches, it has always been a challenging problem. In this paper, an approach f...
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ISBN:
(纸本)9781509047611;9781509047604
Automatic traffic sign detection and recognition (TSDR) is one of the most significant areas of object detection. In spite of numerous researches, it has always been a challenging problem. In this paper, an approach for detecting circular and triangular traffic signs is proposed. The performance of the entire system is measured on German traffic sign detection benchmark (GTSDB) and German traffic sign recognition benchmark (GTSRB) dataset. Traffic signs are detected using color segmentation and thresholding method in Hue Saturation Intensity (HSI) color space. Then, the shape of traffic signs is detected using geometric invariant Hu moments. Further, the features are extracted using a technique called HSI-HOG descriptor where features are extracted from each channel of HSI independently. To select the most discriminant features with minimal loss of information, dimensionality reduction technique Principal Component Analysis (PCA) is applied and classification is performed using Support Vector Machine (SVM) technique.
Oil spill pollution is a severe environmental problem that persists in the marine environment and in inland water systems around the world. Remote sensing is an important part of oil spill response. The hyperspectral ...
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ISBN:
(纸本)9781510604797;9781510604803
Oil spill pollution is a severe environmental problem that persists in the marine environment and in inland water systems around the world. Remote sensing is an important part of oil spill response. The hyperspectral images can not only provide the space information but also the spectral information. Pixels of interests generally incorporate information from disparate component that requires quantitative decomposition of these pixels to extract desired information. Oil spill detection can be implemented by applying hyperspectral camera which can collect the hyperspectral data of the oil. By extracting desired spectral signature from hundreds of band information, one can detect and identify oil spill area in vast geographical regions. There are now numerous hyperspectral imageprocessingalgorithms developed for target detection. In this paper, we investigate several most widely used target detection algorithm for the identification of surface oil spills in ocean environment. In the experiments, we applied a hyperspectral camera to collect the real life oil spill. The experimental results shows the feasibility of oil spill detection using hyperspectral imaging and the performance of hyperspectral imageprocessingalgorithms were also validated.
To increase the efficiency of the laser coagulation surgery the problem of the most accurate segmentation of fundus images is especially relevant. Fundus image segmentation is carried out with high accuracy using effe...
To increase the efficiency of the laser coagulation surgery the problem of the most accurate segmentation of fundus images is especially relevant. Fundus image segmentation is carried out with high accuracy using effective features and the minimum number of parameters for segmentation of a single image fragment. This paper describes a modified technique for smart textural feature selection to extract retinal regions of interest using image preprocessingalgorithms. Preprocessingalgorithms significantly influence the selected features which provide a minimum error of object recognition. In addition image preprocessingalgorithms provide a more precise object selection. The informativeness of the obtained feature space is studied using discriminant data analysis. The best fragmentation block size segmentation and feature sets provides the necessary accuracy to identify regions of interest. Those regions are determined by the analysis of the following 4 classes of fundus images: exudates, thick, thin vessels and healthy areas. The advantages and disadvantages of the considered preprocessingalgorithms were identified.
A holographic data storage system(HDSS) is very important field in the storage system device. Many researchers study the HDSS about imageprocessing algorithm for reduction of image noise. In this work, we proposed an...
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ISBN:
(纸本)9780791849880
A holographic data storage system(HDSS) is very important field in the storage system device. Many researchers study the HDSS about imageprocessing algorithm for reduction of image noise. In this work, we proposed an intelligence virtual mask, parameter values of virtual image mask generated using DNA coding method, it is available to decrease the IPI noise in HDSS. In this paper, an intensity distribution of laser beam in our HDSS is controlled by the virtual mask with an intelligence algorithm. The virtual mask value is changed arbitrarily in real-time with suggested DNA coding method in the HDSS.
This work introduces an Artificial Neuro-Fuzzy Inference System functioning as a selector of color constancy algorithms for the enhancement of dark images. The system selects among three algorithms, the White-Patch, t...
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ISBN:
(纸本)9781509008704
This work introduces an Artificial Neuro-Fuzzy Inference System functioning as a selector of color constancy algorithms for the enhancement of dark images. The system selects among three algorithms, the White-Patch, the Gray-World and the Gray-Edge according to real content of an image. These three algorithms have been considered due to their simplicity and accurate remotion of the illuminant, further showing an outstanding color enhancement on images. The diverse image features are involved in the selection process, so the design of selector system is not a trivial task. For this reason we developed a fuzzy rule based system to model the information through simple rules. While addressing the problem of dark image enhancement this approach can handle large amount of data and is tolerant to ambiguity.
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