Rotation-Invariant Character Recognition by the Moments Using Associated Legendre Functions

スポンサーリンク

概要

• 論文の詳細を見る

• In case of pattern recognition, the extraction of rotation invariant features is a very important problem. In dealing with this problem by the method of moments, Zernike moments as orthogonal complex moments are effective. In this paper, new orthogonal complex moments using associated Legendre functions of the first kind are introduced and they address rotation invariant recognition of images. The principal aim of this paper is placed upon exhibiting the individual characteristics of the new moments. First of all, the accumulation methods are discussed. In addition, the range of degree to be dealt with each moments set is investigated. As the final step, alphabetical character recognition experiments are conducted through various computer simulations.

• 東海大学の論文

著者

• Kawabe Hidekazu

  Department Of Electronics

• Kawabe Hidekazu

  Department Of Electronics School Of Engineering

関連論文

• Rotation-invariant Digital Pattern Recognition Using Singular Value Decomposition Applied Complex-log Mapping
• Handwritten Character Recognition Using Tchebychev Moments and Pseudo-Zernike Moments
• Recognition of Rotated Images Using Complex-log Mapping
• Rotation-Invariant Character Recognition by the Moments Using Associated Legendre Functions
• Recognition of Rotated Images Using Singular Value Decomposition Applied to Complex-log Mapping
• Character Recognition by a Neural Network Using Pseudo-Zernike Moments as Input Data

スポンサーリンク