Rohit Maurya, Dr. Shalini Singh, Dr. P.R Gupta, Manish Kumar Sharma Centre for Development of Advance Computing B-30, Institutional Area, Sector- 62, Noida, India Email: [email protected]Email: [email protected]Email: [email protected]Email: [email protected]Abstract — In this paper we proposed the method for road extraction. The road extraction involves the two main steps: the detection of road that might have the other non road parts like buildings and parking lots followed by morphological operations to remove the non road parts based on their features. We used the K-Means clustering to detect the road area and may be some non road area. Morphological operations are used to remove the non road area based on the assumptions that road regions are an elongated area that has largest connected component. Index Terms — K-Means clustering, morphological operatio ns, road extraction, segmentatio n. I.INTRODUCTIONHE road extraction from digital images has drawn a special attention in the last few decades. Numerous methods has been developed which includes semi automatic and automatic road extraction. Road extraction plays a very important role in vehicle navigation system, urban planning, disaster management system and traffic management system. Semi automatic road extraction required requires userinteraction in order to extract the road where automatic method requires no user interaction. In existing method of road extraction various semi automatic and automatic methods have been developed. Karin K. Hedman, U. Stilla, G. Lisini, P. Gamba (2010) [1] has used two road extractors one for rural areas and another forurban areas. They used two steps for road extraction: first is line extraction followed by a smoothening and splitting step and in another step linear features are evaluated on theirattributes using Bayesian probability theory. Hui Kong, J.-Y. Audibert, J. Ponce (2010) [2] has developed the method based upon the vanishing point associated with main part of road, followed by the segmentation of the corresponding road area based upon the detected vanishing point. Anil and Natarajan (2010) [3] have developed the method based upon statistical region merging [9] for image segmentation and road networkis Figure 1. Roads in developing suburban area extracted based upon skeleton pruning method based on discrete curve evaluation. Yinghua He, Hong Wang, Bo Zhang (2003) [4] has developed an algorithm composed ofthe segmentation of the corresponding road area based upon the detected vanishing point. Anil and Natarajan (2010) [3] have developed the method which uses statistical region merging [9] fo r image segmentation and road is e xtracted using skeleton pruning which is based on contourpartitioning. Yinghua He, Hong Wang, Bo Zhang (2003) [4] has developed an algorithm consists of two major points: boundaries are estimated based on the intensity image and road areas are detected based on the full color image. Tomoko Tateyama, Zensho Nakao, Xian Yan Zeng, Yen-Wei Chen Road Extraction Using K-Means Clustering and Morphological Operations T Rohit Maurya et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES Vol No. 5, Issue No. 2, 290 - 295 ISSN: 2230-7818 @ 2011 http://www.ijaest.iserp.org. All rights Reserved. Page 290
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28.IJAEST Vol No 5 Issue No 2 Raod Extraction Using k Means Clustering and Morphological Operations 290 295
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8/7/2019 28.IJAEST Vol No 5 Issue No 2 Raod Extraction Using k Means Clustering and Morphological Operations 290 295
[5] Tomoko Tateyama, Zensho Nakao, Xian Yan Zeng, Yen-Wei Chen,"Segmentation of High Resolution Satellite Images by Direction andMorphological Filters," his, pp.482-487, Fourth International Conferenceon Hybrid Intelligent Systems (HIS'04), 2004.
[10] Jalal, A. A Fuzzy Model for Road Identification in Satellite Images.Proceedings of the 2006 International Conference on Image Processing,
Computer Vision, & Pattern Recognition, Las Vegas, Nevada, USA, 2006.[11] Anil Z Chitade, Dr. S.K. Katiyar, “Color Based Image Segmentation
using K-Means Clustering”, International Journal of Engineering Scienceand Technology Vol. 2(10), 2010, 5319-5325
[12] C. Heipke, H. Mayer, C. Wiedemann, and O. Jamet. Evaluation of automatic road extraction. In International Archives of Photogrammetryand Remote Sensing, volume 323-4W2, pages 151-160, 1997.
[13] Harvey, W.A., 1999. Performance evaluation for road extraction.
Bull. Soc. Franc Photogrammet. Tele detection 153 (1999-1), 79–87.
[14] Suman Tatiraju, Avi Mehta “Image Segmentation using kmeans clustering
, EM and Normalized Cuts”, University Of California Irvine . .
Rohit Maurya et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIESVol No. 5, Issue No. 2, 290 - 295
ISSN: 2230-7818 @ 2011 http://www.ijaest.iserp.org. All rights Reserved. Page 294
8/7/2019 28.IJAEST Vol No 5 Issue No 2 Raod Extraction Using k Means Clustering and Morphological Operations 290 295