A Comparative Study of Design of Hough Transform Implementation with two Different Methods

Line detection is very important task in image processing field. It is mainly used in auto focusing camera input sensors. Many techniques used for line detection but gives improper result if noise is present in an input image. Hough transform is famous technique present for line detection which gives proper results in presence of noise and discontinuous shapes in an image. This paper gives comparative study of two techniques of hough transform, both the methods are simulated in Xilinx 13.2 design suite which is popularly used for FPGA hardware implementation and compared there simulation results. First method is general hough transform, this is very basic method of hough transform in which binary feature image is given as input and vote procedure of hough transform is performed over it. Second method is given by Zhong-Ho Chen, Alvin W. Y. Su, and Ming-Ting Sun in august 2012, this method use incrementing property of hough transform and process all pixels in parallel. Also locality of hough transform is used to reduce the size of vote memory