A novel single-pass thinning algorithm and an effective set of performance criteria

Intelligent Systems Laboratory, School of Applied Science, Nanyang Technological University, Nanyang Avenue, Singapore 2263, Singapore
Pattern Recognition Letters (Impact Factor: 1.55). 12/1995; 16(12):1267-1275. DOI: 10.1016/0167-8655(95)00078-X
Source: DBLP


A new sequential thinning algorithm, which uses both flag map and bitmap simultaneously to decide if a boundary pixel can be deleted, as well as the incorporation of smoothing templates to smooth the final skeleton, is proposed in this paper. Three performance measurements are proposed for an objective evaluation of this novel algorithm against a set of well established techniques. Extensive result comparison and analysis are presented in this paper for discussion.

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Available from: Chai Quek, Oct 04, 2015
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    • "While some researchers have developed sequential algorithms [6]–[9], the main focus is in parallel thinning algorithms [2], [10]–[13], which are efficient and fast. Raju and Xu [14] in their study of parallel thinning algorithms compared Zhang-Suen, Guo-Hall and One Pass Thinning Algorithm (OPTA) for character recognition. "
    Information Security South Africa Conference 2011, Hyatt Regency Hotel, Rosebank, Johannesburg, South Africa, August 15-17, 2011. Proceedings ISSA 2011; 01/2011
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    • "results in a black and white image with white pixels for bacteria and black pixels for background. The image is then thinned to single pixel width by applying two common skeletonization algorithms in sequence -firstly that of Zhou et al. [3], then that of Zhang and Suen [4]. Once this process has produced a skeleton image, algorithms are applied to identify tip points and branch points. "
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    ABSTRACT: Streptomycetes are soil-based bacteria which exhibit fungal-like filamentous growth patterns and are an important source of medic- inal antibiotics. Despite their usefulness, there are large gaps in our understanding of the mechanisms of growth and branching that they employ. Our research has focussed on analysis and mod- elling of the early stage morphology of the model organism Strep- tomyces coelicolor. To enable this work, we have developed a software tool to provide automatic analysis of microscope images of filamentous microbes. In this paper, we describe the techniques employed in the tool and present some early results from experi- ments we have carried out to quantify the differences between the wild-type and a number of mutants developed at UEA.
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    • "So it can be used for the calculation of the length of the tree trunk, but also for the tree diameter calculation . There were studied and tested numerous skeletonization algorithms for 2D pictures described in (Riazanoff et al., 1990, Sirjani and Cross, 1991, Ge and Fitzpatrick, 1996, Dyer Charles and Rosenfeld, 1979, Bräunl et al., 1995, Pavlidis, 1990, Zamperoni , 1989, Klette and Zamperoni, 1995, Datta and Parui, 1994), but the best result was achieved by the Zhou suggested technique (Zhou et al., 1995). This algorithm was modified to become 1 pixel wide line structures as to reduce the (2 × 2)-structures on the digital picture. "
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