A Class Of Iterative Thresholding Algorithms For Real-Time Image Segmentation
M.H. Hassan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1989
Thresholding algorithms are developed for segmenting gray-level images under nonuniform illumination. The algorithms are based on learning models generated from recursive digital filters which yield to continuously varying threshold tracking functions. A real-time region growing algorithm, which locates the objects in the image while thresholding, is developed and implemented. The algorithms work in a raster-scan format, thus making them attractive for real-time image segmentation in situations requiring fast data throughput such as robot vision and character recognition.