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Proceedings Paper

Features - Description And Extraction For Images With Contours
Author(s): Krishnan R. Tampi; Chetlur S. Sridhar
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Paper Abstract

Images are divided into equal area cells. The contour encountered in these cells are given WORD names, which describe the type of contour. Each cell has 9 pixels in a 3x3 matrix format and herutthere are a possible 512 different WORDs. However, for a class of images where the outline is sufficient for recognition purposes, a much smaller number actually exists. These images include lower case English handwriting and blood cell images. It is shown in this work that there are only 34 BASIC WORDs and all the others encountered in these images are rotations of these BASIC WORDs. Using this fact,features are defined for this class of images, standardized in size to 16 cells described above. Three types of features are defined namely, Independent, Dependent and Related to aid in application of syntactic methods of recognition from sentence structures defined using the above features. It is also shown that matrix algebra can be used for developing data reduction and recognition algorithms.

Paper Details

Date Published: 10 September 1987
PDF: 6 pages
Proc. SPIE 0768, Pattern Recognition and Acoustical Imaging, (10 September 1987); doi: 10.1117/12.940289
Show Author Affiliations
Krishnan R. Tampi, Cochin University of Science and Technology (India)
Chetlur S. Sridhar, Cochin University of Science and Technology (India)

Published in SPIE Proceedings Vol. 0768:
Pattern Recognition and Acoustical Imaging
Leonard A. Ferrari, Editor(s)

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