期刊名称：ELCVIA: electronic letters on computer vision and image analysis
印刷版ISSN：1577-5097
出版年度：2004
卷号：4
期号：1
页码：1-10
出版社：Centre de Visió per Computador
摘要：In this paper, an image segmentation method based on Dempster-Shafer evidence theory is proposed. Basic probability assignment (bpa) is estimated in unsupervised way using pixels fuzzy membership degrees derived from image histogram. No assumption is made about the images data distribution. bpa is estimated at pixel level. The effectiveness of the method is demonstrated on synthetic and real images. keywords: image segmentation and image extraction, Data fusion, Basic probability assignment, Demspter-Shafer evidence
关键词：image segmentation and image extraction;Data fusion;Basic probability assignment;Demspter-Shafer evidence
