loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
18th International Conference on Pattern Recognition (ICPR'06) Volume 2
Classification of Line and Character Pixels on Raster Maps Using Discrete Cosine Transformation Coefficients and Support Vector Machine
Hong Kong
August 20-August 24
ISBN: 0-7695-2521-0
Yao-Yi Chiang, University of Southern California
Craig A. Knoblock, University of Southern California
Raster maps are widely available on the Internet. Valuable information such as street lines and labels, however, are all hidden in the raster format. To utilize the information, it is important to recognize the line and character pixels for further processing. This paper presents a novel algorithm using 2-D Discrete Cosine Transformation (DCT) coefficients and Support Vector Machines (SVM) to classify the pixels of lines and characters on raster maps. The experiment results show that our algorithm achieves 98% precision and 85% recall in classifying the line pixels and 83% precision and 96% recall in classifying the character pixels on a variety of raster map sources.
Citation:
Yao-Yi Chiang, Craig A. Knoblock, "Classification of Line and Character Pixels on Raster Maps Using Discrete Cosine Transformation Coefficients and Support Vector Machine," icpr, vol. 2, pp.1034-1037, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006
Usage of this product signifies your acceptance of the Terms of Use.