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Proceedings Paper

Image Recognition By The Kolmogorov Complexity Program
Author(s): Tsing - Yee Tu; Chialo Ma; Yung - Lung Ma
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Paper Abstract

In this paper we shall consider the intrinsic complexity of patterns and the extent to which this notion is well defined. Past work in the computer science and artificial intelligence literature on the decomposition of pictures into their basic building blocks is consistent with our motivation, but this paper will look at the simplest description over all possible methods. Thus, the program complexity of Kolmogorov given the domain is mini-mum in finite length such that a Turing Machine can compute functions in finite time. So, the string approach is well used as Kolmogorov process. The Circular Layer Chart for Recognition (CLCR) is created with total number of elements (29,-1)*4, where L is the number of layers counted from innermost cell in even 2.1 number. A sequence of string arrays, called Circular Layer String Arrays (CLSA), are achieved for each layer. In this paper there are twenty layers used for the recognition of human face pictures. The distance between both arrays of corresponding layers of test pattern and sample is calculated. The inner five layers are applied for the normalization of orientation. That is, if any of these inner layers does not match, the arrays of test pattern are rotated one position and tried again until they are rotated one circle. If any array of inner layers does not match through the normalization of orientation, the sample is rejected. Thus it can save much time for matching.

Paper Details

Date Published: 10 September 1987
PDF: 8 pages
Proc. SPIE 0768, Pattern Recognition and Acoustical Imaging, (10 September 1987); doi: 10.1117/12.940288
Show Author Affiliations
Tsing - Yee Tu, National Taiwan University (Taiwan)
Chialo Ma, National Taiwan University (Taiwan)
Yung - Lung Ma, National Taiwan University (Taiwan)

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

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