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J. Imaging 2017, 3(3), 29; https://doi.org/10.3390/jimaging3030029

Pattern Reconstructability in Fully Parallel Thinning

Department of Electrical Engineering, Yuan Ze University, Chungli, Taoyuan 320, Taiwan
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Received: 16 June 2017 / Revised: 13 July 2017 / Accepted: 15 July 2017 / Published: 19 July 2017
(This article belongs to the Special Issue Computer Vision and Pattern Recognition)

Abstract

It is a challenging topic to perform pattern reconstruction from a unit-width skeleton, which is obtained by a parallel thinning algorithm. The bias skeleton yielded by a fully-parallel thinning algorithm, which usually results from the so-called hidden deletable points, will result in the difficulty of pattern reconstruction. In order to make a fully-parallel thinning algorithm pattern reconstructable, a newly-defined reconstructable skeletal pixel (RSP) including a thinning flag, iteration count, as well as reconstructable structure is proposed and applied for thinning iteration to obtain a skeleton table representing the resultant thin line. Based on the iteration count and reconstructable structure associated with each skeletal pixel in the skeleton table, the pattern can be reconstructed by means of the dilating and uniting operations. Embedding a conventional fully-parallel thinning algorithm into the proposed approach, the pattern may be over-reconstructed due to the influence of a biased skeleton. A simple process of removing hidden deletable points (RHDP) in the thinning iteration is thus presented to reduce the effect of the biased skeleton. Three well-known fully-parallel thinning algorithms are used for experiments. The performances investigated by the measurement of reconstructability (MR), the number of iterations (NI), as well as the measurement of skeleton deviation (MSD) confirm the feasibility of the proposed pattern reconstruction approach with the assistance of the RHDP process. View Full-Text
Keywords: hidden deletable point (HDP); image processing; pattern reconstruction; reconstructable skeletal pixel (RSP); skeleton; thinning hidden deletable point (HDP); image processing; pattern reconstruction; reconstructable skeletal pixel (RSP); skeleton; thinning
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Chen, Y.-S.; Chao, M.-T. Pattern Reconstructability in Fully Parallel Thinning. J. Imaging 2017, 3, 29.

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