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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Spermatogonium image recognition using Zernike moments.
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Spermatogonium image recognition using Zernike moments.

机译：利用Zernike矩识别精子。

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摘要

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.
机译：精原虫图像的自动识别和分类是生物医学工程研究中非常重要的问题。本文提出了一种精原细胞识别的方案，其中泽尔尼克矩用于表示图像特征。首先，采用数学形态学方法提取每个图像中完整的单个细胞，然后对这些二进制图像进行归一化。然后，从这些归一化图像中计算出Zernike矩，然后通过使用欧几里得距离计算由Zernike矩组成的向量的相似度来识别精原细胞。实验结果表明，所提出的基于Zernike矩的方法优于基于Hu矩和边界矩的两种著名方法。该方法具有较强的区分能力，在区分细胞图像是否属于同一细胞方面表现出更好的性能。

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