文章基本信息

标题：A Hybrid Morphological Active Contour for Natural Images
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作者：Victoria L. Fox ; Mariofana Milanova ; Salim Al-Ali 等
期刊名称：International Journal of Computer Science, Engineering and Applications (IJCSEA)
印刷版ISSN：2231-0088
电子版ISSN：2230-9616
出版年度：2013
卷号：3
期号：4
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Morphological active contours for image segmentation have become popular due to their lowcomputational complexity coupled with their accurate approximation of the partial differential equationsinvolved in the energy minimization of the segmentation process.In this paper, a morphological activecontour which mimics the energy minimization of the popular Chan-Vese Active Contourwithout Edges iscoupled with a morphological edge-driven segmentation termto accurately segmentnatural images. Byusing morphological approximations of the energy minimization steps, the algorithm has a lowcomputational complexity. Additionally, the coupling of the edge-based and region-based segmentationtechniques allows the proposed method to be robust and accurate. We will demonstrate the accuracyandrobustness of the algorithm using images from the Weizmann Segmentation Evaluation Database andreport on the segmentation results using theSorensen-Dice similarity coefficient
关键词：Natural Images;Segmentation;Hybrid Contour;Morpholog;y; Active Contours; Object Extraction