A Swift and Memory Efficient Hough Transform for Systems with Limited Fast Memory

This paper focuses on implementation of a speedy Hough Transform (HT) which considers the memory constraints of the system. Because of high memory demand, small systems (DSPs, tiny robots) cannot realize efficient implementation of HT. Keeping this scenario in mind, the paper discusses an effective and memory-efficient method of employing the HT for extraction of line features from a gray scale image. We demonstrate the use of a circular buffer for extraction of image edge pixels and store the edge image in a manner that is different from the conventional way. Approximation of the two dimensional Hough Space by a one dimensional array is also discussed. The experimental results reveal that the proposed algorithm produces better results, on small and large systems, at a rapid pace and is economical in terms of memory usage.