Generation of moment invariants and their uses for character recognition

Wai Hong Wong; Wan Chi Siu; Kin Man Lam

doi:10.1016/0167-8655(94)00089-L

Generation of moment invariants and their uses for character recognition

Wai Hong Wong, Wan Chi Siu, Kin Man Lam

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

65 Citations (Scopus)

Abstract

An automatic approach for the generation of moment invariants is presented. By making use of this approach a complete set of moment invariants is generated, many of which have never been reported in the literature. This approach will guarantee not to miss any possible expression that may be useful for pattern recognition. Consequently, the generated sets of moment invariants, including higher-order moments, have been used for the recognition of English alphabets. We also include the results of our study on selecting the best set of weighting factors for invariant moments, such that we have improved the recognition rates to over 98.8%.

Original language	English
Pages (from-to)	115-123
Number of pages	9
Journal	Pattern Recognition Letters
Volume	16
Issue number	2
DOIs	https://doi.org/10.1016/0167-8655(94)00089-L
Publication status	Published - 1 Jan 1995

Keywords

Euclidean classification
Moment invariants
Weighting factor

ASJC Scopus subject areas

Artificial Intelligence
Computer Vision and Pattern Recognition
Signal Processing
Software
Electrical and Electronic Engineering

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10.1016/0167-8655(94)00089-L

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AB - An automatic approach for the generation of moment invariants is presented. By making use of this approach a complete set of moment invariants is generated, many of which have never been reported in the literature. This approach will guarantee not to miss any possible expression that may be useful for pattern recognition. Consequently, the generated sets of moment invariants, including higher-order moments, have been used for the recognition of English alphabets. We also include the results of our study on selecting the best set of weighting factors for invariant moments, such that we have improved the recognition rates to over 98.8%.

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KW - Weighting factor

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Generation of moment invariants and their uses for character recognition

Abstract

Keywords

ASJC Scopus subject areas

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