A Class Of Iterative Thresholding Algorithms For Real-Time Image Segmentation

TLDR: A real-time region growing algorithm, which locates the objects in the image while thresholding, is developed and implemented in a raster-scan format, making them attractive for real- time image segmentation in situations requiring fast data throughput such as robot vision and character recognition.

Abstract: 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.