Texture Segmentation Using Voronoi Polygons

Textures are defined in terms of primitives called tokens. A texture segmentation algorithm based on the Voronoi tessellation is discussed. The algorithm first builds the Voronoi tessellation of the tokens that make up the textured image. It then computes a feature vector for each Voronoi polygon. These feature vectors are used in a probabilistic relaxation labeling on the tokens, to identify the interior and the border regions of the textures. Some experimental results are shown. >

[1]  A. Rosenfeld,et al.  A Theory of Textural Segmentation , 1983 .

[2]  Georges Voronoi Nouvelles applications des paramètres continus à la théorie des formes quadratiques. Deuxième mémoire. Recherches sur les parallélloèdres primitifs. , 1908 .

[3]  Flavio R. Dias Velasco A method for the analysis of Gaussian-like clusters , 1980, Pattern Recognit..

[4]  B. Julesz Textons, the elements of texture perception, and their interactions , 1981, Nature.

[5]  Narendra Ahuja,et al.  Extraction of early perceptual structure in dot patterns: Integrating region, boundary, and component gestalt , 1989, Comput. Vis. Graph. Image Process..

[6]  André Gagalowicz,et al.  Blind texture segmentation , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[7]  H. Wilson,et al.  Computation of geometrical and inertial properties for general areas and volumes of revolution , 1976 .

[8]  Wilson S. Geisler,et al.  Texture segmentation using Gabor modulation/demodulation , 1987, Pattern Recognit. Lett..

[9]  Michael Ian Shamos,et al.  Closest-point problems , 1975, 16th Annual Symposium on Foundations of Computer Science (sfcs 1975).

[10]  Narendra Ahuja,et al.  Extracting Perceptual Structure in Dot Patterns: An Integrated Approach , 1987 .

[11]  Béla Julesz,et al.  Visual Pattern Discrimination , 1962, IRE Trans. Inf. Theory.

[12]  Roderick Urquhart,et al.  Graph theoretical clustering based on limited neighbourhood sets , 1982, Pattern Recognit..

[13]  William H. Press,et al.  Numerical Recipes in FORTRAN - The Art of Scientific Computing, 2nd Edition , 1987 .

[14]  M.,et al.  Statistical and Structural Approaches to Texture , 2022 .

[15]  Ramalingam Chellappa,et al.  Decision rules for choice of neighbors in random field models of images , 1981 .

[16]  Steven W. Zucker,et al.  On the Foundations of Relaxation Labeling Processes , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  N. Ahuja,et al.  Representation and Three-Dimensional Interpretation of Image Texture: An Integrated Approach , 1987 .

[18]  Jacob Beck,et al.  Spatial frequency channels and perceptual grouping in texture segregation , 1987, Comput. Vis. Graph. Image Process..

[19]  Rama Chellappa,et al.  Estimation and choice of neighbors in spatial-interaction models of images , 1983, IEEE Trans. Inf. Theory.

[20]  Azriel Rosenfeld,et al.  Scene Labeling by Relaxation Operations , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[21]  Godfried T. Toussaint,et al.  The relative neighbourhood graph of a finite planar set , 1980, Pattern Recognit..

[22]  Anil K. Jain,et al.  A spatial filtering approach to texture analysis , 1985, Pattern Recognit. Lett..

[23]  B Julesz,et al.  Inability of Humans to Discriminate between Visual Textures That Agree in Second-Order Statistics—Revisited , 1973, Perception.

[24]  John F. O'Callaghan,et al.  An Alternative Definition for "Neighborhood of a Point" , 1975, IEEE Transactions on Computers.

[25]  Larry S. Davis,et al.  An Empirical Evaluation of Generalized Cooccurrence Matrices , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Anil K. Jain,et al.  Markov Random Field Texture Models , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  Edward A. Patrick,et al.  Interactive Use of Problem Knowledge for Clustering and Decision Making , 1971, IEEE Transactions on Computers.

[28]  R. Hummel,et al.  Toward a low-level description of dot clusters: Labeling edge, interior, and noise points , 1979 .

[29]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[30]  Charles T. Zahn,et al.  Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters , 1971, IEEE Transactions on Computers.