Orthogonal moments based texture analysis of CT liver images

Authors:
V. Subbiah Bharathi;L. Ganesan
Affiliations:
Department of Computer Science and Engineering, DMI College of Engineering, Chennai 602 103, Tamil Nadu, India;Department of Computer Science and Engineering, A.C. College of Engineering and Technology, Karaikudi 623 004, Tamil Nadu, India
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

Orthogonal moments such as Zernike moments and Legendre moments have been proven to have superior feature representation capability and low information redundancy. The number of orthogonal moments to be used as features or numerical attributes to perform any application is minimal due to the orthogonal nature. However, the information possessed by each moment order needs to be analysed to identify the appropriate moment orders for the undertaken task. In this work, a statistical significance test has been performed to select the best moment orders to discriminate normal and abnormal tissues in liver images. The experimental results reveal the efficacy of the proposed features.