Segmentation engine: a real-time image segmentation subsystem
Byron Dom, W. E. Blanz, Charles Cox, David A. Steele, Alan D. Dorundo · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
This paper describes a system developed for segmenting multiband grayscale images into n-class labeled images at high-throughput rates. This system, which we refer to as the segmentation engine, performs supervised image segmentation using algorithms based on the statistical pattern recognition paradigm. So-called 'features' are computed for each pixel and the feature vector thus formed is presented to a statistical classifier, which uses feature information to determine the most probable class of the pixel. Algorithms are described for the following: features, automatic feature selection, classification and classifier training. While this paper describes the entire system, the algorithmic approach will be emphasized.