Image Retrieval Method Based on Vision Feature of Color

Abstract

Color histogram is an important technique for color database retrieving, but it often ignores color’s spatial distribution information. This paper proposes an improved color histogram algorithm based on the HSV space, whose subspaces are non-equally quantized. The algorithm first proceeds annular partition on the original image, and then uses the method presented by Aibing Rao etc. [1] to count each partition. At last, it calculates the weighted sums for the distances between distinct color histograms. Experimental results demonstrate that the algorithm reduces the feature dimensions and keeps a good accuracy as well as the spatial distribution information. Thus, a better retrieval result is obtained.

Image retrieval based on swarm intelligence

“…Then the distance between the distinct colored histogram is calculated. When implemented, better retrieval results are obtained [14].…”

“…The color scheme consists of three parts: hue, saturation, value. This system of colors is used to extract the characteristics of colors, as images are converted from RGB color system to HSV color system [14]. Annular color moment according to distribution of interest points, annular division is easy to obtain.…”