{"title":"A novel boundary approach for shape representation and classification","authors":"L. Sumalatha, B. Sujatha, P. Sreekanth","doi":"10.1109/ICCCNT.2013.6726673","DOIUrl":null,"url":null,"abstract":"Shape is an important visual feature and it is one of the basic features used to describe image content. However, shape representation and classification is a difficult task. This paper presents a new boundary based shape representation and classification algorithm based on mathematical morphology. It consists of two steps. Firstly, an input shape is represented by using Hit Miss Transform (HMT) into a set of structuring elements. Secondly, the extracted shape of the image is classified based on shape features. Experimental results show that the integration of these strategies significantly improves shape database.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"158 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2013.6726673","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Shape is an important visual feature and it is one of the basic features used to describe image content. However, shape representation and classification is a difficult task. This paper presents a new boundary based shape representation and classification algorithm based on mathematical morphology. It consists of two steps. Firstly, an input shape is represented by using Hit Miss Transform (HMT) into a set of structuring elements. Secondly, the extracted shape of the image is classified based on shape features. Experimental results show that the integration of these strategies significantly improves shape database.
形状是一种重要的视觉特征，是描述图像内容的基本特征之一。然而，形状表示和分类是一项艰巨的任务。提出了一种基于数学形态学的基于边界的形状表示与分类算法。它包括两个步骤。首先，使用HMT (Hit Miss Transform)将输入形状表示为一组结构元素。其次，根据形状特征对提取的图像形状进行分类;实验结果表明，这些策略的集成显著改善了形状数据库。
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