K3M: A universal algorithm for image skeletonization and a review of thinning techniques

Abstract

This paper aims at three aspects closely related to each other: first, it presents the state of the art in the area of thinning methodologies, by giving descriptions of general ideas of the most significant algorithms with a comparison between them. Secondly, it proposes a new thinning algorithm that presents interesting properties in terms of processing quality and algorithm clarity, enriched with examples. Thirdly, the work considers parallelization issues for intrinsically sequential algorithms of thinning. The main advantage of the suggested algorithm is its universality, which makes it useful and versatile for a variety of applications.

Bengali Printed Character Recognition – A New Approach

“…For this purpose authors used KMM algorithm [25]. In this approach the character image was thinned to a skeleton form before applying view-based method to extract features.…”

Character Recognition Based on Skeletonization: A Survey.

“…The algorithm is combined between parallel and sequential which categorized under the iterative approach [24] Iterative techniques, the Peeling contour process iteratively parallels or sequentially; in a parallel way, the whole unwanted pixels are erased after identifying the whole wanted pixels Whereas in sequential techniques; the unwanted pixels are removed in the identifying the desired pixels in each iteration. In a non-iterative approach, the skeleton is extracted directly without examining each pixel individually, but these techniques are difficult to implement and slow as well [25]. The algorithm for thinning has been extensively tested on several Devanagari script characters [26].…”

A Novel Approach To Topological Skeletonization Of English Alphabets And Characters

“…Paper by [4] showed an efficient use of iterative algorithms. Comprehensive work by [6] and [7] also helped us understand the morphological operations in greater details.…”