Scene classification using adaptive processing of tree representation of rectangular-shape partition of images

Wei Sun, Ken Lo, Zheru Chi

Research output: Journal article publicationConference articleAcademic researchpeer-review


Image classification is very helpful for organizing large image data-bases and content based image retrieval (CBIR). However, it is very complex and challenging because of lacking effective methods. In this paper, we present a tree representation of images based on rectangular-shape partition. Then an adaptive processing algorithm is adopted to perform the classification task. Experimental results on seven categories of scenery images show that the structural representations are better than the traditional methods and our previous work based on quadtree representation of fixed partition.
Original languageEnglish
Pages (from-to)274-280
Number of pages7
JournalLecture Notes in Computer Science
Issue numberII
Publication statusPublished - 26 Sep 2005
EventSecond International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 - Chongqing, China
Duration: 30 May 20051 Jun 2005

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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