Results 281 to 290 of about 1,230,227 (332)
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986
An edge in an image corresponds to a discontinuity in the intensity surface of the underlying scene. It can be approximated by a piecewise straight curve composed of edgels, i.e., short, linear edgeelements, each characterized by a direction and a position.
V S, Nalwa, T O, Binford
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An edge in an image corresponds to a discontinuity in the intensity surface of the underlying scene. It can be approximated by a piecewise straight curve composed of edgels, i.e., short, linear edgeelements, each characterized by a direction and a position.
V S, Nalwa, T O, Binford
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IEEE Journal on Robotics and Automation, 1986
Edge operators based on gray-scale morphologic operations are introduced. These operators can be efficiently implemented in near real time machine vision systems which have special hardware support for gray-scale morphologic operations. The simplest morphologic edge detectors are the dilation residue and erosion residue operators.
J.S.J. Lee, R.M. Haralick, L.G. Shapiro
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Edge operators based on gray-scale morphologic operations are introduced. These operators can be efficiently implemented in near real time machine vision systems which have special hardware support for gray-scale morphologic operations. The simplest morphologic edge detectors are the dilation residue and erosion residue operators.
J.S.J. Lee, R.M. Haralick, L.G. Shapiro
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986
Edge detection is the process that attempts to characterize the intensity changes in the image in terms of the physical processes that have originated them. A critical, intermediate goal of edge detection is the detection and characterization of significant intensity changes. This paper discusses this part of the edge detection problem. To characterize
V, Torre, T A, Poggio
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Edge detection is the process that attempts to characterize the intensity changes in the image in terms of the physical processes that have originated them. A critical, intermediate goal of edge detection is the detection and characterization of significant intensity changes. This paper discusses this part of the edge detection problem. To characterize
V, Torre, T A, Poggio
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A Cooperating Edge Grammar for Edge Detection
1997Edge detection is a fundamental process in many low-level vision algorithms. It generates a concise and a compact description of the image structure, suitable for manipulation in computer vision tasks. In this paper we describe an application of Cellular Automata to the reconstruction of edges in an image.
G. Adorni +2 more
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Applied Optics, 1977
Edge detection and enhancement are required in a number of important image processing applications. In this paper we consider the problem of optimizing spatial frequency domain filters for detecting a class of edges in images. The filter is optimum in that it produces maximum energy in the vicinity of the location of the edge for a given spatial ...
F M, Dickey, K S, Shanmugam
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Edge detection and enhancement are required in a number of important image processing applications. In this paper we consider the problem of optimizing spatial frequency domain filters for detecting a class of edges in images. The filter is optimum in that it produces maximum energy in the vicinity of the location of the edge for a given spatial ...
F M, Dickey, K S, Shanmugam
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Computer Graphics and Image Processing, 1980
Publisher Summary This chapter discusses the problem of detecting edges in cellular textures. Detecting edges is an important first step in the solution of many image analysis tasks. Edges are used primarily to aid in the segmentation of an image into meaningful regions, but they are also extensively used to compute relatively local measures of ...
LARRY S. DAVIS, AMAR MITICHE
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Publisher Summary This chapter discusses the problem of detecting edges in cellular textures. Detecting edges is an important first step in the solution of many image analysis tasks. Edges are used primarily to aid in the segmentation of an image into meaningful regions, but they are also extensively used to compute relatively local measures of ...
LARRY S. DAVIS, AMAR MITICHE
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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 ...
Zhou, Jie, Peng, Jiaxiong, Ding, Mingyue
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IEEE Transactions on Image Processing, 1994
The paper presents a new parametric model-based approach to high-precision composite edge detection using orthogonal Zernike moment-based operators. It deals with two types of composite edges: (a) generalized step and (b) pulse/staircase edges. A 2-D generalized step edge is modeled in terms of five parameters: two gradients on two sides of the edge ...
S, Ghosal, R, Mehrotra
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The paper presents a new parametric model-based approach to high-precision composite edge detection using orthogonal Zernike moment-based operators. It deals with two types of composite edges: (a) generalized step and (b) pulse/staircase edges. A 2-D generalized step edge is modeled in terms of five parameters: two gradients on two sides of the edge ...
S, Ghosal, R, Mehrotra
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Proceedings of the Royal Society of London. Series B. Biological Sciences, 1980
A theory of edge detection is presented. The analysis proceeds in two parts. (1) Intensity changes, which occur in a natural image over a wide range of scales, are detected separately at different scales. An appropriate filter for this purpose at a given scale is found to be the second derivative of a Gaussian, and it is shown that ...
D, Marr, E, Hildreth
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A theory of edge detection is presented. The analysis proceeds in two parts. (1) Intensity changes, which occur in a natural image over a wide range of scales, are detected separately at different scales. An appropriate filter for this purpose at a given scale is found to be the second derivative of a Gaussian, and it is shown that ...
D, Marr, E, Hildreth
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International Journal of Pattern Recognition and Artificial Intelligence, 1998
The paper describes a technique called ISE for image segmentation using entropy. The relation between the entropy of an image domain and the entropy of its subdomains is explored as a uniformity predicate. Such entropy is obtained from the analysis of the image histogram associating a Gaussian distribution to the maximum frequency of gray levels.
Vitulano, S. +2 more
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The paper describes a technique called ISE for image segmentation using entropy. The relation between the entropy of an image domain and the entropy of its subdomains is explored as a uniformity predicate. Such entropy is obtained from the analysis of the image histogram associating a Gaussian distribution to the maximum frequency of gray levels.
Vitulano, S. +2 more
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