Content-based image retrieval using color features of salient regions
Jaehyun An, Sang Hwa Lee, Nam Ik Cho · 2014
This paper presents a content-based color image retrieval system based on color features from the salient regions and their spatial relationship. The proposed method first extracts the salient regions by a color contrast method, and finds several dominant colors for each region. Then, the spatial distribution of each dominant color is described as a binary map. Specifically, the salient region is partitioned into small sub-blocks, and each sub-block is assigned as 1 or 0 according to the number of pixels corresponding to the dominant color. The set of binary maps define the spatial distribution of dominant colors within and across the salient regions, which approximately reflect the objects' shapes and the spatial relationship of the objects. A simple matching method for this description is also proposed, which needs very few computations for each image matching. According to the experiments with several widely used color image databases, the proposed method shows better retrieval performance than the state-of-the-art and previous color-based methods. The proposed algorithm is suitable for color image retrieval on the web and mobile systems, because it needs very few computations which are mostly binary logical operations.