A neural network approach to color image classification

Masayuki Shinmoto, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

Research output: Contribution to journalConference article

Abstract

This paper presents a method for image classification by neural networks which uses characteristic data extracted from images. In order to extract characteristic data, image pixels are divided by a clustering method on YCrCb 3-dimensionl-color space and processed by labeling to select domains. The information extracted from the domains is characteristic data (color information, position information and area information) of the image. Another characteristic data, which is extracted by Wavelet transform, is added to the feature and a comparative experiment is conducted. Finally the validity of this technique is verified by means of computer simulations.

Original languageEnglish
Pages (from-to)617-622
Number of pages6
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2773 PART 1
Publication statusPublished - 2003 Dec 1
Event7th International Conference, KES 2003 - Oxford, United Kingdom
Duration: 2003 Sep 32003 Sep 5

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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