Spermatogonium image recognition using Zernike moments

Authors:
Wang Liyun;Ling Hefei;Zou Fuhao;Lu Zhengding;Wang Zhendi
Affiliations:
College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;Department of Urology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
Venue:
Computer Methods and Programs in Biomedicine
Year:
2009

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Abstract

The automatic identification and classification of spermatogonium images is a very important issue in biomedical engineering research. This paper proposes a scheme for spermatogonium recognition, in which Zernike moments are used to represent image features. First of all, the mathematical morphology method is employed to extract the intact individual cell in every image, and then we normalize these binary images. Then, Zernike moments are calculated from these normalized images, followed by recognizing the spermatogonia through computing similarity of vectors composed with Zernike moments using Euclidean distance. Experimental results demonstrate that the proposed method, based on Zernike moments, outperforms two well-known methods, namely those based on Hu moments and boundary moments. This method has stronger distinguishing ability, showing better performance in discriminating cell images whether belong to the same cell.