DocumentCode :
144680
Title :
An integrating KFCM and threshold segmentation fusion method for contour lines extraction from color scanned topographical maps
Author :
Xiao-ning Li ; Min Fu ; Shi-ying Wang
Author_Institution :
Coll. of Comput. Sci., Sichuan Normal Univ., Chengdu, China
Volume :
2
fYear :
2014
fDate :
26-28 April 2014
Firstpage :
987
Lastpage :
991
Abstract :
Extracting contour lines from digital maps is a difficult problem which is often encountered when building a geographic information system. In this paper, a fusion algorithm which integrates kernel fuzzy C means (KFCM) clustering technique and threshold segmentation technique is presented to automatically extract the contour lines. Firstly, color image of scanned topographical map is converted into HIS color space. Then its corresponding feature image is constructed by using its saturation channel data from HIS space and its space information image together. Finally segmentation threshold value is calculated by applying KFCM clustering algorithm and threshold segmentation method is implemented to extract contour lines. Experimental results show that the fusion algorithm can overcome the segmentation difficulties from the color diffusion phenomenon. No matter the distribution of grayscale image is unimodal, bimodal, or multimodal, the method can effectively extract the contour lines from color map images.
Keywords :
cartography; geographic information systems; image colour analysis; image fusion; image segmentation; pattern clustering; HIS color space; KFCM clustering algorithm; KFCM clustering technique; color diffusion phenomenon; color image; color map images; color scanned topographical maps; contour lines extraction; digital maps; feature image; fusion algorithm; geographic information system; grayscale image; integrating KFCM; kernel fuzzy C means clustering technique; saturation channel data; segmentation difficulty; segmentation threshold value; space information image; threshold segmentation fusion method; threshold segmentation method; threshold segmentation technique; Algorithm design and analysis; Clustering algorithms; Colored noise; Feature extraction; Image color analysis; Image segmentation; contour lines extraction; digital topographical map; kernel fuzzy C means clustering; threshold segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science, Electronics and Electrical Engineering (ISEEE), 2014 International Conference on
Conference_Location :
Sapporo
Print_ISBN :
978-1-4799-3196-5
Type :
conf
DOI :
10.1109/InfoSEEE.2014.6947816
Filename :
6947816
Link To Document :
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