{"title":"Active Contours with Thresholding Value for Image Segmentation","authors":"Gang Chen, Haiying Zhang, I-Ping Chen, Wen Yang","doi":"10.1109/ICPR.2010.555","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an active contour with threshold value to detect objects and at the same time get rid of unimportant parts rather than extract all information. The basic ideal of our model is to introduce a weight matrix into region-based active contours, which can enhance the weight for the main parts while filter the weak intensity, such as shadows, illumination and so on. Moreover, we can choose threshold value to set weight matrix manually for accurate image segmentation. Thus, the proposed method can extract objects of interest in practice. Coupled partial differential equations are used to implement this method with level set algorithms. Experimental results show the advantages of our method in terms of accuracy for image segmentation.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 20th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2010.555","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper, we propose an active contour with threshold value to detect objects and at the same time get rid of unimportant parts rather than extract all information. The basic ideal of our model is to introduce a weight matrix into region-based active contours, which can enhance the weight for the main parts while filter the weak intensity, such as shadows, illumination and so on. Moreover, we can choose threshold value to set weight matrix manually for accurate image segmentation. Thus, the proposed method can extract objects of interest in practice. Coupled partial differential equations are used to implement this method with level set algorithms. Experimental results show the advantages of our method in terms of accuracy for image segmentation.