Image feature extraction algorithm for robotic applications: Region features case

This paper presents an image feature extraction algorithm for robotic applications. The proposed method robust against scene illumination change, viewpoint change, specularity, colour saturation, imperfect focus of image, and shadows. The proposed algorithm is a bottom up approach which consists of three phases: colour classification, correction, and description. In colour classification phase, chrominance (CIE Lab colour space) is used to segment coloured images in order to detect potential coloured region. Thresholding and several morphological operations are applied in correction phase in order to eliminate the noise pixels. Finally, moment method is used to identify the desired image features (area, position and orientation) of targets. The results are presented to illustrate each operations involved and demonstrate the performance of proposed image feature extraction algorithm. Overall, the proposed method is suitable for known operating environment cases where a robot operates in predefined workspace with prior knowledge of target.