An IFCE-based effective color tracking system for a humanoid robot in cluttered environments
Xiaoqian Mao, Huidong He, Wei Li, Genshe Chen · 2017
A variety of object tracking algorithms have been published in the field of image process, but most of them are easily influenced by illumination intensity and may not be reliable in cluttered environments. This paper proposes a novel color tracking system by extracting an object of interest with color similarities, which is based on an Improved Fuzzy Color Extractor (IFCE). The IFCE uses the angle between two vectors to distinguish the two pixels in RGB space coordinates. The length of a vector represents the illumination intensity of the pixel and the direction corresponds to the color. Thus, the illumination intensity and the color of a pixel are separated to adapt IFCE varying illumination conditions. Moreover, the strict color discrimination is accomplished by setting the fuzzy parameters. The central vision tracking strategy performs dynamic tracking processes. We use the NAO robot to validate the proposed system by tracking a moving person with several color tags. The results show that the IFCE-based color tracking system is robust in the cluttered environment with varying illumination intensity and the NAO robot tracks the person effectively.