Color Feature Based Dominant Color Extraction

Abstract

The dominant colors in an image can be used for image search, color editing, palette generation, and several other applications. Conventionally, dominant colors are extracted using clustering or histogram-based methods. However, these methods cannot extract the dominant colors of small regions, which are essential for the analysis of color schemes. This study developed an approach to automatically extract dominant colors based on color features that are typically considered by human observers when analyzing color schemes. The proposed method first calculates the initial dominant color candidates using the K-means algorithm in the CIELAB color space and the graph cut of a region adjacency graph (RAG) of the segmented image. Next, the algorithm calculates the color features such as the saturation, contrast, and area of each cluster, based on which it extracts the dominant colors. Our method can extract prominent colors from small image regions as the dominant colors, which is not possible using conventional methods.

Keywords

• Color
• image color analysis
• image processing