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Journal of Emerging Trends in Computing and Information Sciences >> Call for Papers Vol. 8 No. 3, March 2017

Journal of Emerging Trends in Computing and Information Sciences

Extraction of ROI in Geographical Map Image

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Author Mehnaz Tabassum, Mohammad Shorif Uddin
ISSN 2079-8407
On Pages 237-242
Volume No. 2
Issue No. 5
Issue Date May 01, 2011
Publishing Date May 01, 2011
Keywords k-means, image segmentation, ROI, map image processing, transportation network


Extraction of Region of Interest (ROI) from geographical map image is an important task of document analysis and recognition. The extracted segments are applied to different machine vision and embedded system. The task is very complex because of having overlapping objects, intersected lines etc in map. Keeping this in mind, the present thesis paper describes two methods that have been applied to extract efficient ROI for both road network and waterway from geographical map; one is color based segmentation applying K-means clustering and other is template based matching which overcome the previous limitations. Different from the existent methods, these proposed approaches are efficient both in segmentation results and further reconstruction also. And our experimental results are close to human perceptions; therefore our methods provide better and more robust performance than either of the individual methods. We hope these methods will find diverse applications in ROI extraction from geographical map and also image analysis.  


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