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.
|ジャーナル||Proceedings of the IEEE International Conference on Systems, Man and Cybernetics|
|出版物ステータス||Published - 2000 12 1|
|イベント||2000 IEEE International Conference on Systems, Man and Cybernetics - Nashville, TN, USA|
継続期間: 2000 10 8 → 2000 10 11
ASJC Scopus subject areas
- Control and Systems Engineering
- Hardware and Architecture