A Straight Line Detection Based on Randomized Method

Detecting lines from a digital image is very important in image processing. An efficient line detection based on randomized method is presented. Different from the previous HT (Hough Transform) based methods which vote on a parameter space, this algorithm does not need an accumulator for representing parameter space. The main concept in the proposed method is: firstly, it selects two different edge points from an edge image to form a candidate line; secondly, under the given distance tolerance, a strip image region along the candidate line direction can be got, then the number of edge points in the determined image strip region is accumulated; and lastly, the threshold rules will be applied to further determine whether the candidate line is the desired one. Experimental results show that this approach can accurately find the lines in noisy images. Compared with HT and RHT (Randomized Hough Transform), the proposed algorithm has the advantages of fewer storage space and shorter computational time.