Global And Local Feature Extraction Based On Circular Scanning Of The Images
Vojislav Divljakovic · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
Circular scanning of the images provides efficient and simple way of feature extraction of 2D images. Such features are insensitive to object's position,orientation and scale. In vision systems employing sensors with random access of pixels ( CIDs or Optic RAMs) features can be extracted by readout of sensor's data. The main disadvantage of the method is the same as for the concept of polar projections ( Radon transform) - such features do not uniquely describe shape of objects. In the situations where objects show variation of gray scale value inside their boundaries, it is possible to identify regions of uniform gray scale and perform local feature extraction of such regions using the same technique of circular scanning. Simultaneous execution of some stages of process for local and global features is possible, thus enabling their efficient extraction . Instead of one feature vector per object, a set of feature vectors is achievable, and hierarchical relation between global and local feature vectors enables fast and accurate classification of objects.