An Iterative Thinning Algorithm for Binary Images Based on Sequential and Parallel Approaches

Abstract

Thinning is an important process in several applications of computer vision. It aims to find the onepixel midline of the pattern in binary image. In spite of different thinning methods that have been proposed, the existing methods are not capable of solving all thinning problems. In this work, a new iterative thinning method for binary images was proposed based on a hybrid technique of sequential and parallel approaches. It consists of three stages. The first pre-processing stage determined and prepared the contour. Next, the peeling stage tested and removed unwanted pixels. When the first two stages did not meet more pixels, the postprocessing stage prepared the skeleton to produce the final one-pixel width skeleton. In this work, the first and last stages adopted the sequential approach, while the second stage was based on the parallel approach. To evaluate the performance of the proposed method, a selected and DIBCO2010-H_DIBCO2010_GT benchmark datasets were used with benchmark measurement techniques for thinning processing. The results were compared with Huang, Zhang, K3M, and Abu-Ain methods. The experiments show that the proposed method is implemented well with all types of thinning problems, better than other methods. It is simple to design, its result skeleton has one-pixel width, and it preserves the topology and connectivity.