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dc.contributor.authorTari, Abdelkamel-
dc.contributor.authorSider, Abderrahmane-
dc.contributor.authorBen Boudaoud, Lynda-
dc.date.accessioned2022-12-29T12:31:08Z-
dc.date.available2022-12-29T12:31:08Z-
dc.date.issued2015-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/5-
dc.descriptionIn image processing, image thinning is a fundamental preprocessing step that plays a vital role in many applications such as pattern recognition, finger print classification, medical applications etc. The thinning process transforms an input binary image into a skeleton by reducing the original image which contains different thicknesses to a thin representation (a set of curves and lines). The notion of the skeleton was originally defined by Blum in 1962 [1] through an analogy with grass-fire. If we imagine an object as a grass field and we set on fire on the border of the field, the fire will start propagating inside the field and when fire fronts meet, they vanish. The meeting points of the flame fronts would constitute the skeleton of the object.en_US
dc.description.abstractAbstract—Thinning plays a crucial role in image analysis and pattern recognition applications. It is one of the most frequently used pre-processing methods to analyze different types of images. Thinning consists basically of reducing a thick digital object into a thin skeleton. There are several thinning algorithms for getting a skeleton of a binary image in the literature. The most popular, and well proved one is the ZS algorithm proposed by Zheng and Suen. In the present paper, we propose a new thinning algorithm which combines the directional approach used by ZS and the subfield approach in order to produce a new hybrid thinning algorithm which is more efficient, produces thinner results (skeleton thickness is equal to one) than the ZS algorithm and solves the ZS’s loss of connectivity problem in 2×2 squares. Results of applying the proposed algorithm on a variety of binary images and comparison with ZS algorithm show better results in terms of thinning rate, thinning speed, visual quality and connectivity preservation.en_US
dc.language.isoenen_US
dc.publisherIEEE Xploreen_US
dc.relation.ispartofseriesaestin2;2-
dc.subjectThinningen_US
dc.subjectalgorithmen_US
dc.subjectBinaryen_US
dc.subjectimagesen_US
dc.subjectSkeletonen_US
dc.subjectSkeletonen_US
dc.subjectParallelen_US
dc.subjectthinningen_US
dc.subjectIterativeen_US
dc.subjectthinningen_US
dc.subjectThinningen_US
dc.subjectrateen_US
dc.subjectThinningen_US
dc.subjectspeeden_US
dc.titleA New Thinning Algorithm for Binary Imagesen_US
dc.typeOtheren_US
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