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The Link Between Image Segmentation and Image Recognition.

机译:图像分割和图像识别之间的联系。

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摘要

A long standing debate in computer vision community concerns the link between segmentation and recognition. The question I am trying to answer here is, Does image segmentation as a preprocessing step help image recognition? In spite of a plethora of the literature to the contrary, some authors have suggested that recognition driven by high quality segmentation is the most promising approach in image recognition because the recognition system will see only the relevant features on the object and not see redundant features outside the object (Malisiewicz and Efros 2007; Rabinovich, Vedaldi, and Belongie 2007). This thesis explores the following question: If segmentation precedes recognition, and segments are directly fed to the recognition engine, will it help the recognition machinery? Another question I am trying to address in this thesis is of scalability of recognition systems. Any computer vision system, concept or an algorithm, without exception, if it is to stand the test of time, will have to address the issue of scalability.
机译:长期以来,计算机视觉界一直在争论细分与识别之间的联系。我在这里想要回答的问题是,图像分割作为预处理步骤是否有助于图像识别?尽管有大量相反的文献,但一些作者建议,由高质量分割驱动的识别是图像识别中最有前途的方法,因为识别系统只会看到对象上的相关特征,而看不到外部的多余特征。对象(Malisiewicz和Efros 2007; Rabinovich,Vedaldi和Belongie 2007)。本文探讨了以下问题:如果在识别之前进行分段,并且将分段直接输入到识别引擎,它将对识别机制有帮助吗?我在本文中要解决的另一个问题是识别系统的可伸缩性。任何计算机视觉系统,概念或算法,如果要经受时间的考验,无一例外都必须解决可伸缩性问题。

著录项

  • 作者

    Sharma, Karan.;

  • 作者单位

    Portland State University.;

  • 授予单位 Portland State University.;
  • 学科 Computer Science.
  • 学位 M.S.
  • 年度 2012
  • 页码 72 p.
  • 总页数 72
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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