Design and implementation of a low-level image segmentation architecture-LISA

Abstract

The architectural and implementation issues of a prototype of a low-level image segmentation architecture (LISA) are described. LISA performs real-time gray-level image segmentation. A decision-theoretic pattern recognition approach divided into feature extraction and decision analysis parts is used. The feature extraction part is based on extracting local and global descriptions of the image pixels. In the decision analysis part, the pixels are classified into one of the user-selected classes based on the extracted features. One of the main properties of the approach is that the feature extraction and decision analysis are performed in real time. The status of the hardware and software development of the LISA prototype for a variety of industrial inspection applications is described.