Extracting Boundaries from Images by Comparing Cooccurrence Matrices

Abstract. This paper describes methods of extracting region boundaries from the frames of an image sequence by combining information from spatial or temporal cooccurrence matrices of the frames. It summarizes past work on the uses of cooccurrence matrices for image segmentation; qualitatively describes the peaks (clusters of high values) that can be expected to occur in cooccurrence matrices when the image(s) contain smooth regions separated by stationary or moving boundaries; and describes methods of extracting stationary or moving region boundaries from an image by combining information from spatial and temporal cooccurrence matrices. 1 Cooccurrence matrices and their uses Cooccurrence matrices, originally called gray-tone spatial dependency matrices, were introduced by Haralick et al. [1], who used them to define textural properties of images. Let I be an image whose pixel gray levels are in the range 0, . . . , 255. Let δ = (u, v) be an integer-valued displacement vector; δ spec...

• Type: Conference
• Year: 2003
• Where: DICTA
• Authors: Astrit Rexhepi, Azriel Rosenfeld
• Keywords: Cooccurrence Matrices, DICTA 2003, DICTA 2007, Gray Levels, Temporal Cooccurrence Matrices