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Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines
Gebze Institute of Technology, Dept. of Geodesy and Photogrammetry Engineering, 41400, Gebze, Kocaeli, Turkey
Yildız Technical Univ., Dept. of Geodesy and Photogrammetry Engineering, 34349, Besiktas, Istanbul, Turkey
Kahramanmaras Sutcu Imam Univ., Dept. of Forest Engineering, 46100, Kahramanmaras, Turkey
* Author to whom correspondence should be addressed.
Received: 19 February 2008 / Accepted: 1 April 2008 / Published: 15 April 2008
Abstract: This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately.
Keywords: Raster to vector conversion; geographic information systems; vectorization; thinning; topology; threshold.
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Cite This Article
MDPI and ACS Style
Karas, I.R.; Bayram, B.; Batuk, F.; Akay, A.E.; Baz, I. Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines. Sensors 2008, 8, 2673-2694.
Karas IR, Bayram B, Batuk F, Akay AE, Baz I. Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines. Sensors. 2008; 8(4):2673-2694.
Karas, Ismail R.; Bayram, Bulent; Batuk, Fatmagul; Akay, Abdullah E.; Baz, Ibrahim. 2008. "Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines." Sensors 8, no. 4: 2673-2694.