Neural net based image retrieval by using color and location information

Motomichi Inoue, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

研究成果: Conference article

3 引用 (Scopus)

抜粋

In this paper a neural net-based image retrieval method is presented, in which color and location features are extracted from images. This method can retrieve similar images to a selected one from a large data set of color images. In particular, the location features in the color distribution of an image are important in the image retrieval. This image retrieval method extracts color features and their location information included in an image. A neural network tries to find images with similar features from a data set. First, images are translated into gray-scale ones and then are divided into eight regions based on gray scale values. The color and location features are extracted from these regions after integration of regions. The RGB and HSV color values in each region, area, and X- and Y-values in the orthogonal coordinates are learned by the multi-layered neural network. After learning, the neural network evaluates the similarity between a selected image and the other ones in the data set. Similar images found by the neural network are retrieval results.

元の言語English
ページ(範囲)2575-2579
ページ数5
ジャーナルProceedings of the IEEE International Conference on Systems, Man and Cybernetics
4
出版物ステータスPublished - 2000 12 1
外部発表Yes
イベント2000 IEEE International Conference on Systems, Man and Cybernetics - Nashville, TN, USA
継続期間: 2000 10 82000 10 11

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

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