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  • 标题:Synergy between Object Recognition and Image Segmentation
  • 本地全文:下载
  • 作者:Y.Ramadevi ; B.Kalyani ; T.Sridevi
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2010
  • 卷号:2
  • 期号:8
  • 页码:2767-2772
  • 出版社:Engg Journals Publications
  • 摘要:Image segmentation is to partition an image into meaningful regions with respect to a particular application. Object recognition is the task of finding a given object in an image or video sequence. This paper discusses the interaction between image segmentation and object recognition in the framework of the Expectation-Maximization (EM) algorithm. Threshold is image processing technique for converting grayscale or color image to a binary image based upon a threshold value. The OTSU method is one of the applied methods of image segmentation in selecting threshold automatically for its simple calculation and good adaptation. Genetic Algorithms (GAs) tries to find structure in data that might seem random, or to make a seemingly unsolvable problem more or less 'solvable'. In this paper a synergy between Image segmentation and object recognition using EM algorithm, OSTU and GA.
  • 关键词:EM algorithm; OSTU; Genetic Algorithm; Image Segmentation; Object Recognition.
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