Efficient feature extraction method applied to the OCR of Persian digits

Details Efficient feature extraction method applied to the OCR of Persian digits Efficient feature extraction method applied to the OCR of Persian digits

Oct 1997

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1997spie.3164..169l&link_type=abstract

Proc. SPIE Vol. 3164, p. 169-178, Applications of Digital Image Processing XX, Andrew G. Tescher; Ed.

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In this paper, a method will be described for reduction of an n-dimensional feature vector into a 2D feature vector. Reaching for this goal, a structure is introduced, referred to as the chaining structure, which is generated from the initial n-dimensional feature vector. The proposed technique can be though as a feature extraction method. The simplicity and the consistency of the technique beside the fact that the resulted feature set is of 2D, are the main advantages of the proposed method. It will also be illustrated how a specially designed neural network can be used to implement the proposed method. The efficiency of the proposed feature extraction algorithm will be illustrated by applying the method to the OCR of handwritten Persian digits. Finally, it will be compared with principal component analysis.

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