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Pattern Recognition using Normalized Feature Vectors Analysis


  • Department of Computer science, Guru Kashi University, Talwandi Sabo – 151302, Punjab, India


Objective: To study pattern recognition and retrieval in machine vision system application. Methods/Analysis: Regular and irregular pattern recognition algorithm based on sorting of radii from centre of mass is used and other tools such as Matlab, Neural networks. Findings: The radii from centre of mass to contour of the pattern are computed and sorted in descending order. Few top radii are taken for recognition of the given pattern. As the radii are sorted in descending order, therefore, if the pattern is orientated at any angle, the top order radii are same. This enables the pattern recognition at any orientation. Further, the radii are normalized with respect to their mean radius to make them size invariant. In addition, area, perimeter and euler number are also computed for enhancing the uniqueness degree in features vector set.


CBIR, Extraction, Normalization, NN.

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