Title: Object recognition with discrete orthogonal Hahn moments

Authors: Fatima Akhmedova; Simon Liao

Addresses: DMT Systems Development Group, Winnipeg, MB, Canada ' Department of Computer Science, University of Winnipeg, Winnipeg, MB, Canada

Abstract: In this research, we have analysed the image feature descriptive properties of discrete orthogonal Hahn moments, and proposed a new object recognition scheme with three modes of Hahn moment descriptors, global, local, and hybrid, respectively. For each mode, we have employed the four highest variances values from ten lowest order of Hahn moments to compose a four-dimensional feature vector. To clarify our new scheme of using discrete orthogonal Hahn moment characteristics, we utilised a set of 6,763 Chinese characters defined in China's national standard GB2312, with the font of song, as the testing object set. Each of the three Hahn moment modes has performed very well, while the experimental results of utilising the three Hahn moment modes are independent from each other.

Keywords: discrete orthogonal Hahn moments; object recognition; Chinese character recognition.

DOI: 10.1504/IJAPR.2017.089389

International Journal of Applied Pattern Recognition, 2017 Vol.4 No.4, pp.329 - 341

Received: 02 Feb 2017
Accepted: 17 Apr 2017

Published online: 22 Jan 2018 *

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