文章基本信息

标题：A Study of Active Contour Segmentation Models based on Automatic Initial Contour
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作者：Caibo1 ; Zhigui Liu ; Junbo Wang 等
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2015
卷号：8
期号：4
页码：201-214
DOI：10.14257/ijsip.2015.8.4.18
出版社：SERSC
摘要：Image segmentation is a fundamental and challenging problem in image processing and often a vital step for high level analysis. Due to the active contour model (ACM) need to choose the initial contour for the following evolution, it limited the utilities of this kind of segmentation to a large extent. For the purpose of avoiding the processing of human choosing initial contour, in this paper, we proposed an automatic initial contour choosing algorithm of the input image information. Based on the chosen initial contour, the iterative efficient and the accuracy of segmentation have been improved when the initial contour is incorporated into the local based segmentation framework. Extensive experiments on synthetic and real images are provided to evaluate our method, showing significant improvements on the segmentation accuracy and stability, comparing to the human chosen initial contour, such as LBF and LGIF.
关键词：Image segmentation; ACM model; Curve evolution; Initial contour; LBF; ; LGIF