A Novel Method for Object Recognition under Varying Illumination

Abstract

A novel method of image segmentation was proposed in this paper to realize robustness and quickness in object recognition under varying illuminations. This method uses a seven-color flower (SCF) model based on a complete RGB space to realize dynamic tracking of the clustering parameters. The experiments of image segmentation under varying illuminations indicate that this model can not only make color segmentation real-time and robust but also meet the requirement of object recognition for autonomous mobile robot without prior environmental knowledge.