Application of Fuzzy C-Means Algorithm in Complex Background Image Segmentation of Forensic Science

被引：1

作者：

Chen, Zhuang ^{[1
]}

Li, ChunYu ^{[1
]}

Jiang, ZhanQing ^{[1
]}

Zhao, Yongqiang ^{[1
]}

机构：

[1] Univ China PPSUC, Peoples Publ Secur, Forens Image Technol Direct, 1 South Muxidi Lane, Beijing Xicheng Dist, Peoples R China

来源：

COMMUNICATIONS, SIGNAL PROCESSING, AND SYSTEMS, CSPS 2018, VOL III: SYSTEMS | 2020年 / 517卷

关键词：

Image segmentation; Fuzzy C-Means; Forensic science; Stamp impression; Complex background;

D O I：

10.1007/978-981-13-6508-9_27

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the field of forensic science, image segmentation is required as a basic and significant stage in forensic image analysis. It is very important to segment the stamp impression image with a complex background precisely. This paper puts forward a feasible and efficient approach for complex background stamp impression image segmentation based on Fuzzy C-Means (FCM) algorithm. The fuzzy feature of forensic image can be handled efficiently using Fuzzy C-Means (FCM) algorithm in the forensic science field. The results of the experiments demonstrate the validity and accuracy of Fuzzy C-Means (FCM) algorithm.

引用

页码：212 / 217

页数：6

共 8 条

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