AUTOMATIC LOCAL SEGMENTATION TECHNIQUE FOR DETECTION OF ROAD SURFACE CRACK

dc.contributor.author	RIYADI, SLAMET
dc.date.accessioned	2018-03-23T02:19:02Z
dc.date.available	2018-03-23T02:19:02Z
dc.date.issued	2016
dc.identifier.issn	2393-2835
dc.identifier.uri	http://repository.umy.ac.id/handle/123456789/18155
dc.description.abstract	Image processing technique has been implemeted to detect the crack on road surface. However, the accuracy of the detection is still low due to the difficulties in segmentation between crack and non-crack area. This research proposes the implementation of Sauvola technique to perform automatic local segmentation of crack. The methodology involves preprocessing, image segmentation, feature extraction and classification step. In segmentation step, in addition to Sauvola, other techniques, i.e. manual thresholding, Otsu and Bernsen, are also implemented for comparison purpose. The result shows that Sauvola technique produces consistent segmentation results on high, medium and low quality images. Sauvola method also perform the best accuracy detection of 96% among them.	en_US
dc.subject	Image Processing	en_US
dc.subject	Road Surface Crack	en_US
dc.subject	Segmentation	en_US
dc.subject	Sauvola Technique	en_US
dc.subject	Thresholding	en_US
dc.title	AUTOMATIC LOCAL SEGMENTATION TECHNIQUE FOR DETECTION OF ROAD SURFACE CRACK	en_US

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