High‐precision γ‐ω hough transformation algorithm to detect arbitrary digital lines

Abstract

AbstractThe γ‐ω Hough transform we proposed earlier (a) does not lead to bias in the number of votes accumulated in the cell even when the parameter space is sampled in uniform cells and voting takes place over all pixels, and (b) the voting locus becomes a piecewise linear line composed of two segments so drawing and analyzing the curve is simple. These are significant advantages. In a conventional γ‐ω Hough transformation algorithm, however, votes from the pixel set included on one digital line spread over multiple cells in the parameter space and the number of pixels forming digital lines is not always taken as the correct number of votes. The reason is the conventional algorithm does not detect all of the target digital lines in the image space. In this research, for the γ‐ω Hough parameter space, we determine the cell configuration having a one‐to‐one correspondence with all of the digital lines in the image space and demonstrate an appropriate voting method for this cell configuration. By applying the “high‐precision γ‐ω Hough transformation algorithm” used in the cell configuration and voting method proposed in this paper, digital lines having any orientation and position can be stably and precisely detected.