2-dimensional object recognition for the ISAC system

The intelligent soft arm control (ISAC) system is a voice-activated robotic aid for the physically disabled which involves the requirement for object recognition. The authors present a brief description of the ISAC system and describe work in 2-D object recognition and orientation. The research in object recognition involves the extraction of relevant information from digitized images. A binary image was processed by a nonrecursive segmentation algorithm to isolate each object. Next, two histograms were generated for each object found by the segmentation routine: a distance histogram about the object´s center of mass and an orientation histogram. The distance histogram was used for identification of objects and the orientation histogram was used for finding their orientation. Additionally, a nonrecursive segmentation algorithm, a histogram-based recognition and orientation detection algorithm and a multivariate-discriminant-analysis-based recognition algorithm are described