Neural net based image retrieval by using color and location information

Abstract

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 the X- and Y-values in the orthogonal coordinates are learned by a multi-layered neural network. After learning, the neural network evaluates the similarity between a selected image and the other ones in the data set. The similar images found by the neural network are the retrieval results.