HOUGH TRANSFORM WITH DYNAMIC THRESHOLDING FOR ROBUST AND REAL-TIME DETECTION OF COMPLEX CURVES IN IMAGES

Abstract

A dynamic thresholding method is proposed for use in the Hough transform to detect complex curves in images robustly. While determining edge pixels contributing to the peak in the Hough space for detecting a curve with noise and other errors, the proposed method can endure the errors by detecting pixels coming from an equal-width shape which is centered at the curve with a small width everywhere along the curve. This equal-width shape detection capability is accomplished by the use of a dynamic threshold for pixel selection, which is derived from the use of the first-order directional derivative of the function describing the curve. Three conventional methods are compared to show the superiority in robustness of the proposed method via experimental results, and a real-time application of the method for quick detection of lines in omni-images is also demonstrated.