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

Abstract

The main focus of this paper is on the architectural and implementation issues of a prototype of a low-level image segmentation architecture (LISA). LISA performs real-time (20 Mpixels/sec) gray-level image segmentation, i.e., assignment of image pixels to a few user-selected classes. A decision-theoretic pattern-recognition approach is used, which is divided into a feature extraction part and a decision analysis part. The feature extraction part is based on extracting local and global descriptions for all of the image pixels. In the decision analysis part we designed a novel no-cross-term classifier, which significantly reduced the hardware complexity. The LISA prototype has been built with custom and off-the-shelf VLSI chips. Some measured results will also be reported. © 1993 Springer-Verlag.