期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2014
卷号：5
期号：3
页码：1
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In this contribution, we develop a novel global threshold-based active contour model. This model deploys a newedge-stopping function to control the direction of the evolution and to stop the evolving contour at weak orblurred edges. An implementation of the model requires the use of selective binary and Gaussian filteringregularized level set (SBGFRLS) method. The method uses either a selective local or global segmentationproperty. It penalizes the level set function to force it to become a binary function. This procedure is followed byusing a regularisation Gaussian. The Gaussian filters smooth the level set function and stabilises the evolutionprocess. One of the merits of our proposed model stems from the ability to initialise the contour anywhere insidethe image to extract object boundaries. The proposed method is found to perform well, notably when theintensities inside and outside the object are homogenous. Our method is applied with satisfactory results onvarious types of images, including synthetic, medical and Arabic-characters images.
关键词：Active contour model; Level set method; CV model; ZAC model.
