A Feature Extraction Strategy Based on Multiple Color Information

Abstract

In this paper, a feature extraction strategy based on multiple color information fusion was proposed. Firstly this method started with analyzing the transform formula of color space, which transform was mainly thinking about RGB color space to other color spaces. Secondly by analyzing the characteristic of every color space in describing the actual color information, the advantages and disadvantages of every color space were showed. Thirdly through above conclusion, the algorithm which extracted the target feature only using single color information was defective, and then the strategy based on multiple color information fusion was proposed. Lastly the detail fusion strategy was given, which fused the probability distributed information of multiple color into the last probability distributed information as the target feature. The feature extraction strategy in this paper is verified by the camshift algorithm. The results show that the multiple color information fusion can improve the tracking performance of moving target.