New orientation-based elimination approach for accurate line-detection
Detecting lines correctly from a digital image is an important crucial step in many real-word applications. In this paper, we present an orientation-based strategy to filter out those inappropriate edge pixels before performing the line-detection task. Due to the effective strategy, both the memory size and the computation time are significantly reduced during a Hough transform-based detection process. Further, the proposed elimination strategy can also speed up the randomized-based detection process. Taking four previously developed line-detection techniques as comparison targets, experimental results have shown that our proposed orientation-based elimination strategy is superior to the previous line-detection methods in terms of memory requirement and computation time.
line-detection elimination strategy speed up hough transform orientation-histogram randomized voting