DocumentCode :
3416078
Title :
Color paper map segmentation using eigenvector line-fitting
Author :
Khotanzad, Alireza ; Zink, Edd
Author_Institution :
Image Process. & Anal. Lab., Southern Methodist Univ., Dallas, TX, USA
fYear :
1996
fDate :
8-9 Apr 1996
Firstpage :
190
Lastpage :
194
Abstract :
This paper presents a color segmentation algorithm for paper-based United States geological survey (USGS) topographic maps. The algorithm uses an eigenvector line-fitting technique to overcome false colors introduced by the scanning process due to RGB misalignment. The RGB misalignment is caused by the optical characteristics of the scanner lens and is mostly evident in regions of color change. The resulting false colors render traditional color clustering schemes ineffective. The eigenvector line-fitting approach uses the color information of pixels in a 7 by 7 window to classify the color transitional pixels. This algorithm has been experimentally verified to be robust and accurate
Keywords :
cartography; edge detection; eigenvalues and eigenfunctions; image classification; image colour analysis; image segmentation; RGB misalignment; United States geological survey; color change; color clustering; color information; color paper map segmentation; color segmentation algorithm; color transitional pixels classification; eigenvector line-fitting; false colors; optical characteristics; scanning process; topographic maps; Clustering algorithms; Cultural differences; Image analysis; Image color analysis; Image segmentation; Lenses; Optical filters; Optical refraction; Optical sensors; Roads;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Interpretation, 1996., Proceedings of the IEEE Southwest Symposium on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-3200-8
Type :
conf
DOI :
10.1109/IAI.1996.493751
Filename :
493751
Link To Document :
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