Results 231 to 240 of about 323,476 (264)
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Edge Detection by Adaptive Splitting
Journal of Scientific Computing, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bernardo Llanas, Sagrario Lantarón
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Edge Detection by Helmholtz Principle
Journal of Mathematical Imaging and Vision, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Agnès Desolneux +2 more
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Graphical Models and Image Processing, 1996
Abstract Most of the research in edge detection until now has been based on the classical noisy mono-edge model. In the present paper, we address the noisy multi-edge detection problem. After introducing an elementary noisy multi-edge model, we first propose and analyze a multi-edge model described by the sum of two stationary stochastic processes ...
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Abstract Most of the research in edge detection until now has been based on the classical noisy mono-edge model. In the present paper, we address the noisy multi-edge detection problem. After introducing an elementary noisy multi-edge model, we first propose and analyze a multi-edge model described by the sum of two stationary stochastic processes ...
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2005
In this paper, the Mumford-Shah (MS) model and its variations are studied for image segmentation. It is found that using the piecewise constant approximation, we cannot detect edges with low contrast. Therefore other terms, such as gradient and Laplacian, are included in the models. To simplify the problem, the gradient of the original image is used in
Qinghui Zhang +2 more
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In this paper, the Mumford-Shah (MS) model and its variations are studied for image segmentation. It is found that using the piecewise constant approximation, we cannot detect edges with low contrast. Therefore other terms, such as gradient and Laplacian, are included in the models. To simplify the problem, the gradient of the original image is used in
Qinghui Zhang +2 more
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Graphical Models and Image Processing, 1993
Abstract This paper deals with the problem of extracting edge structure from compressed image representations. As image coding techniques become more common in image manipulation systems, it is reasonable to develop methods of analyzing an image using operations on the compressed image representation rather than the reconstructed image.
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Abstract This paper deals with the problem of extracting edge structure from compressed image representations. As image coding techniques become more common in image manipulation systems, it is reasonable to develop methods of analyzing an image using operations on the compressed image representation rather than the reconstructed image.
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Improved Codebook Edge Detection
Graphical Models and Image Processing, 1995Abstract A technique for detecting edges directly from a vector-quantized image representation, called codebook edge detection was proposed by Mclean (CVGIP: Graphical Models Image Process. 55, 1993, 48-57). With this method, the edges can be detected by a simple table lookup, a so-called "edge codebook." In this paper, we propose an improved method ...
Jie Zhou 0001 +2 more
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Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1990
Abstract In this paper, we have described a new robust edge detection algorithm which performs equally well under a wide variety of noisy situations and a broad range of edges. The algorithm is executed in three phases. In phase 1, the step and linear edges are detected from the noise corrupted image.
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Abstract In this paper, we have described a new robust edge detection algorithm which performs equally well under a wide variety of noisy situations and a broad range of edges. The algorithm is executed in three phases. In phase 1, the step and linear edges are detected from the noise corrupted image.
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Edge Detection and Edge Images
1995This chapter gives a summary of edge detection methods in gray-level images based on [Bru90]. We also introduce unions and bit-fields in C++.
Dietrich W. R. Paulus, Joachim Hornegger
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A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986This paper describes a computational approach to edge detection. The success of the approach depends on the definition of a comprehensive set of goals for the computation of edge points. These goals must be precise enough to delimit the desired behavior of the detector while making minimal assumptions about the form of the solution. We define detection
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MCED Blood Test Boosts Cancer Detection in Symptomatic Patients
Ca-A Cancer Journal for Clinicians, 2023Mike Fillon
exaly