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A Study on Human Eye Detection in a Color Image Based on Harris Corner Detector and Sobel Edge Operator  [PDF]
Dibyendu Ghoshal,Alak Das
International Journal of Electronics Communication and Computer Technology , 2012,
Abstract: A study is made to detect human eye from a color face image (in RGB space) using Harris corner detector and Sobel edge operator. Morphological operation like dilation and erosion are also applied to make the edge of the eyes sharp and prominent. This study is found to yield 90.47% eye detection rate which is comparable with the same obtained by other standard algorithm.
Performance Evaluation of Edge Detection Using Sobel, Homogeneity and Prewitt Algorithms  [PDF]
Abdel Karim M. Baareh, Ahmad Al-Jarrah, Ahmad M. Smadi, Ghazi H. Shakah
Journal of Software Engineering and Applications (JSEA) , 2018, DOI: 10.4236/jsea.2018.1111032
Abstract: Edge detection considered as very important and fundamental tool in image processing. An image edge is a very sensitive place where the image information and details mostly placed on it. Different filters were used to detect and enhance these edges to improve the sharpness and raising the image clarity. The significance of this paper comes from the study, compare and evaluate the effects of three well-known edge detection techniques in a spatial domain, where this evaluation was performed using both subjective and objective manner to find out the best edge detection algorithm. The Sobel, Homogeneity and Prewitt algorithms were used on 2D gray-scale synthesis and real images in Jordan using C# programming language. According to the comparative results obtained using the three techniques, it was clearly found that Prewitt and Homogeneity algorithms performance were better than Sobel algorithm. Therefore, Prewitt and Homogeneity algorithms can be recommended as useful detection tools in edge detection.

YANG Xuan,LIANG Dequn,

自动化学报 , 1999,
Abstract: The most important thing in multiscale edge detection is the filter scale. Region homogeneity measure is defined to distinguish homogenous region from edge region. The cubic B spine wavelet whose scale is adjusted by the region homogeneity measure is used to detect edge. The experiment results and comparisons show that this method is effective and feasible.
Edge Detection Model Based on Involuntary Eye Movements of the Eye-Retina System
András Róka,ádám Csapó,Barna Reskó,Péter Baranyi
Acta Polytechnica Hungarica , 2007,
Abstract: Traditional edge-detection algorithms in image processing typically convolute afilter operator and the input image, and then map overlapping input image regions tooutput signals. Convolution also serves as a basis in biologically inspired (Sobel, Laplace,Canny) algorithms. Recent results in cognitive retinal research have shown that ganglioncell receptive fields cover the mammalian retina in a mosaic arrangement, withinsignificant amounts of overlap in the central fovea. This means that the biologicalrelevance of traditional and widely adapted edge-detection algorithms with convolutionbasedoverlapping operator architectures has been disproved. However, using traditionalfilters with non-overlapping operator architectures leads to considerable losses in contourinformation. This paper introduces a novel, tremor-based retina model and edge-detectionalgorithm that reconciles these differences between the physiology of the retina and theoverlapping architectures used by today's widely adapted algorithms. The algorithm takesinto consideration data convergence, as well as the dynamic properties of the retina, byincorporating a model of involuntary eye tremors and the impulse responses of ganglioncells. Based on the evaluation of the model, two hypotheses are formulated on the highlydebated role of involuntary eye tremors: 1) The role of involuntary eye tremors hasinformation theoretical implications 2) From an information processing point of view, thefunctional role of involuntary eye-movements extends to more than just the maintenance ofaction potentials. Involuntary eye-movements may be responsible for the compensation ofinformation losses caused by a non-overlapping receptive field architecture. In support ofthese hypotheses, the article provides a detailed analysis of the model's biologicalrelevance, along with numerical simulations and a hardware implementation.
An Edge Detection Algorithm for Human Knee Osteoarthritis Images
Prof. Samir K. Bandyopadhyay
Journal of Global Research in Computer Science , 2011,
Abstract: Digital image processing comprises varieties of applications, where some of these used in medical image processing include convolution, edge detection as well as contrast enhancement. Efficient edge detection depends on choosing the threshold; the choice of threshold directly determines the results of edge detection. Osteoarthritis (OA) results from a failure of cells within the joint to maintain the balance between synthesis and degradation of the extracellular matrix. OA is a major cause of pain and disability in the elderly yet there is at present no effective treatment for loss of joint function. This is partly because the condition is heterogeneous with obscure pathogenesis but also because there are no specific laboratory tests or screening procedures that provide a specific diagnosis of early OA. There is a clear need to be able to define onset of characteristic pathological changes when intervention would be timely and to monitor the natural history up to the stage of Radiological detected damage. In this paper, edge detection operator and its enhanced algorithm is used to detect edges for human knee osteoarthritis images in different critical situations. It is shown that the algorithm is very effective in case of noisy and blurs images.
A Study of Edge Detection Method for different Climate Condition Images using Digital Image Processing  [PDF]
P. Balakrishnan,S. Muruganand,K. Sriram
International Journal of Computer Science Issues , 2012,
Abstract: Human eye can sense different weather conditions as same as the sensor. The human eye gives good result. In this proposal work the six different edge detection methods are applied to analyze weather condition. In this work the special kind of changes in the picture for different weather condition are observed. The six different edge detection method like sobel, prewitt, Robert, canny, laplacian of Gaussian and zero crossing are used to analyze the weather condition and finally the result of three methods are compared for best result.
A Color Edge Detection Operator Based on Human Vision System

LIN Sheng you,SHI Jiao ying,

中国图象图形学报 , 2005,
Abstract: Edge detection is one of the basic pre processing methods in digital image processing and computer vision. It is one of the most important algorithms making the processing going further. Edge detection is essentially a problem of color difference computing. Although edge detection has been explored deeply in gray image, it is still a difficult problem in color image for its trouble to define the color difference including not only value, but also direction. In this paper, a new color edge detection algorithm is proposed. This algorithm is based on Human Vision System (HVS) separating the chroma and intensity information of RGB color to emphasize the more important one. Inspired by this important property of HVS, the intensity difference and chroma difference are computed respectively, and then the weighted mean over these two differences is taken as the final color difference. This algorithm solves some problems produced by the existing algorithms and is proved to be a practical and effective color edge detection algorithm.
An Edge Detection Algorithm Based on Integral Transform

WANG Yu sheng,PU Jia jun,CHEN Chun,

中国图象图形学报 , 2002,
Abstract: This paper discusses an integral transform that can be applied to region and edge detection. With homogeneity scale and spatial scale parameters, the transform converts image into vector field showing the attractions among pixels in the image, and thus edge detection can be performed by finding divergent vectors in the field. This paper analyses some problem of applying the transform to edge detection and presents a method of estimating homogeneity scale parameter using local information. Based on the transform and previous work, a simplified version of edge detection algorithm is given. Its experimental results are also presented, with comparison to some classical edge detection algorithm. Its edge detection capability is comparable with Canny edge detection algorithm.
A New Approach for Text Detection Using Fuzzy Homogeneity

Huang Jian-hua Cheng Heng-da Wu Rui Liu Jia-feng,

电子与信息学报 , 2008,
Abstract: Text data presented in images and video contains useful and important semantic information for semantic-based image retrieval system. In this paper, a method is proposed for text detection based on fuzzy logic and homogeneity. First, the original images is fuzzified based on the maximum entropy principle. Then edge and textural information is extracted to evaluate the homogeneity of image which is transformed to fuzzy homogeneity domain. Finally text region is confirmed with texture analysis in fuzzy homogeneity domain. Experimental results confirm that the proposed method achieves better performance in complex background and is applicable to various kinds of video and images.
Edge Detection of Medical Images Using Morpholgical Algorithms  [PDF]
Anurag Sharma,Pankaj Sharma,Rashmi,Hardeep Kumar
International Journal for Science and Emerging Technologies with Latest Trends , 2012,
Abstract: Medical images edge detection is an important work for object recognition of the human organs and it is an important pre-processing step in medical image segmentation and 3D reconstruction. Conventionally, edge is detected according to some early brought forward algorithms such as gradient-based algorithm and template-based algorithm, but they are not so good for noise medical image edge detection. In this paper, basic mathematical morphological theory and operations are introduced at first, and then a novel mathematical morphological edge detection algorithm is proposed to detect the edge of lungs CT image with salt-and-pepper noise. The experimental results show that the proposed algorithm is more efficient for medical image denoising and edge detection than the usually used template-based edge detection algorithms and general morphological edge detection algorithms.
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