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
收藏
页码：212 / 217
页数：6
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