Region-based binary tree representation for image classification

Zhiyong Wang, Dagan Feng, Zheru Chi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Image classification is a very challenging problem due to lack of effective representations. In this paper, a region-based binary tree representation incorporating with adaptive processing of data structures is proposed to address this problem. After an image is segmented, a binary tree is established to characterize its contents by using region merging method. Finally, an adaptive processing of data structure algorithm is employed to perform the classification task with binary tree representation. Experimental results on seven categories of scenery images show this region-based structural representation is superior to our previous work based on quadtree representation.
Original languageEnglish
Title of host publicationProceedings of 2003 International Conference on Neural Networks and Signal Processing, ICNNSP'03
Pages232-235
Number of pages4
Volume1
DOIs
Publication statusPublished - 1 Dec 2003
Event2003 International Conference on Neural Networks and Signal Processing, ICNNSP'03 - Nanjing, China
Duration: 14 Dec 200317 Dec 2003

Conference

Conference2003 International Conference on Neural Networks and Signal Processing, ICNNSP'03
CountryChina
CityNanjing
Period14/12/0317/12/03

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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