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Texture descriptors based on co-occurrence matrices
128
ABSTRACTS
OF PAPERS ACCEPTED
FOR PUBLICATION
describes an algorithm for constructing the perspectiveprojection aspect graph of convex polyhedra. In the perspective projection aspect graph, viewpoint space is modeled as all of 3D space surrounding the object. This makes the perspective projection aspect graph a more realistic representation than the orthographic projection aspect graph, in which viewpoint space is modeled by the Gaussian sphere. The algorithm uses an intermediate data structure which represents a complete parcellation of 3D space derived from the geometric definition of the object. All information necessary for identifying object aspects and corresponding viewing cells is obtained as a result of this parcellation. The resulting aspect graph structure has a node for each distinct aspect/viewing cell. The upper bounds on the time complexity of the algorithm and the space complexity of the resulting data structure are @(N4), where N is the number of faces of the polyhedron. The algorithm has been implemented in C, runs on a SUN workstation, and can use PADL-2 files for its input description of objects. Strip Algorithm in Curve Fitting. MAYLOR K. LEUNG AND YEE-HONG YANG. Department of Computational Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N OWO. Received March 7, 1989; accepted July 12, 1989.
Dyaamic
In this paper, a new technique for fitting a curve with lines employing strips is presented. An interesting feature of the proposed algorithm is its ability to dynamically adjust the direction of the strip to increase the number of contour points that can be enclosed within a strip. This translates to minimizing the number of the generated line segments with little added cost. Texture
Descriptors
Based on Co-occarrence
Matrices.
Department of Computer Science, University Received July 18, 1988; revised May 26, 1989.
CALVIN C. GOTLIEB AND HERBERTE. KREYSWG. of Toronto, Toronto, Ontario, Canada M5S lA4.
This paper focuses on the problem of texture classification using statistical descriptors based on the co-occurrence matrices. A major part of the paper is dedicated to the derivation of a general model for analysis and interpretation of experimental results in texture analysis, when individual and groups of classifiers are being used, and a technique for evaluating their performance. Using six representative classifiers of Haralick, Shanmugan, and Dinstein, that is, second angular moment fl, contrast f2, inverse difference moment f5, entropy f9, and information measures of correlation I and II, fl2 and f13, we give a systematic study of the discrimination power of all 63 combinations of these classifiers on 13 samples of Brodatz textures. The conclusion that can be drawn from our study is that it is useful to combine classifiers up to a certain order. Here it turned out that groups of four classifiers are optimal. Connectivity Is Not Local& Computabik for Connected 30 Images. CHUNG-NIM LEE. Department of Mathematics, Pohang Institute of Science and Technology, P.O. Box 125 Pohang, 790-330 Republic of Korea; AZRIEL ROSENFELD. Center for Automation Research, University of Maryland, College Park, Maryland 20742. Received December 17, 1986; accepted July 12, 1989.
Simple
It is well known that “is connected” is not locally computable for 2D (or, hence, higher-dimensional) images. We show that “is simply connected” and “is contractible” are locally computable for connected images in 2D, but not in 3D. Orientability of a surface is likewise not locally computable.
ABSTRACTS
OF PAPERS ACCEPTED
FOR PUBLICATION
describes an algorithm for constructing the perspectiveprojection aspect graph of convex polyhedra. In the perspective projection aspect graph, viewpoint space is modeled as all of 3D space surrounding the object. This makes the perspective projection aspect graph a more realistic representation than the orthographic projection aspect graph, in which viewpoint space is modeled by the Gaussian sphere. The algorithm uses an intermediate data structure which represents a complete parcellation of 3D space derived from the geometric definition of the object. All information necessary for identifying object aspects and corresponding viewing cells is obtained as a result of this parcellation. The resulting aspect graph structure has a node for each distinct aspect/viewing cell. The upper bounds on the time complexity of the algorithm and the space complexity of the resulting data structure are @(N4), where N is the number of faces of the polyhedron. The algorithm has been implemented in C, runs on a SUN workstation, and can use PADL-2 files for its input description of objects. Strip Algorithm in Curve Fitting. MAYLOR K. LEUNG AND YEE-HONG YANG. Department of Computational Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N OWO. Received March 7, 1989; accepted July 12, 1989.
Dyaamic
In this paper, a new technique for fitting a curve with lines employing strips is presented. An interesting feature of the proposed algorithm is its ability to dynamically adjust the direction of the strip to increase the number of contour points that can be enclosed within a strip. This translates to minimizing the number of the generated line segments with little added cost. Texture
Descriptors
Based on Co-occarrence
Matrices.
Department of Computer Science, University Received July 18, 1988; revised May 26, 1989.
CALVIN C. GOTLIEB AND HERBERTE. KREYSWG. of Toronto, Toronto, Ontario, Canada M5S lA4.
This paper focuses on the problem of texture classification using statistical descriptors based on the co-occurrence matrices. A major part of the paper is dedicated to the derivation of a general model for analysis and interpretation of experimental results in texture analysis, when individual and groups of classifiers are being used, and a technique for evaluating their performance. Using six representative classifiers of Haralick, Shanmugan, and Dinstein, that is, second angular moment fl, contrast f2, inverse difference moment f5, entropy f9, and information measures of correlation I and II, fl2 and f13, we give a systematic study of the discrimination power of all 63 combinations of these classifiers on 13 samples of Brodatz textures. The conclusion that can be drawn from our study is that it is useful to combine classifiers up to a certain order. Here it turned out that groups of four classifiers are optimal. Connectivity Is Not Local& Computabik for Connected 30 Images. CHUNG-NIM LEE. Department of Mathematics, Pohang Institute of Science and Technology, P.O. Box 125 Pohang, 790-330 Republic of Korea; AZRIEL ROSENFELD. Center for Automation Research, University of Maryland, College Park, Maryland 20742. Received December 17, 1986; accepted July 12, 1989.
Simple
It is well known that “is connected” is not locally computable for 2D (or, hence, higher-dimensional) images. We show that “is simply connected” and “is contractible” are locally computable for connected images in 2D, but not in 3D. Orientability of a surface is likewise not locally computable.