{"title":"A new marker-based watershed algorithm","authors":"H. Gao, P. Xue, Weisi Lin","doi":"10.1109/ISCAS.2004.1329213","DOIUrl":null,"url":null,"abstract":"The marker-based watershed approach is a very efficient means for image segmentation and has been widely used in recent years. The conventional marker-based algorithms are realized using hierarchical queues. A new marker-based watershed algorithm based on the disjoint set data structure is proposed in this paper. It consists of two steps: the flooding step and the resolving step. This algorithm has significantly lower memory requirement as compared with the conventional algorithms while maintaining the computational complexity of O(N) where N is the image size. Experimental results further show that the new algorithm implemented in C language runs much faster than the conventional algorithm based on the hierarchical queues as a result of savings from huge memory allocation and releasing operations.","PeriodicalId":6445,"journal":{"name":"2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512)","volume":"18 1","pages":"II-81"},"PeriodicalIF":0.0000,"publicationDate":"2004-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAS.2004.1329213","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 38
Abstract
The marker-based watershed approach is a very efficient means for image segmentation and has been widely used in recent years. The conventional marker-based algorithms are realized using hierarchical queues. A new marker-based watershed algorithm based on the disjoint set data structure is proposed in this paper. It consists of two steps: the flooding step and the resolving step. This algorithm has significantly lower memory requirement as compared with the conventional algorithms while maintaining the computational complexity of O(N) where N is the image size. Experimental results further show that the new algorithm implemented in C language runs much faster than the conventional algorithm based on the hierarchical queues as a result of savings from huge memory allocation and releasing operations.
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