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Classification of Line and Character Pixels on Raster Maps Using Discrete Cosine Transformation Coefficients and Support Vector Machine

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2 Author(s)
Yao-Yi Chiang ; Dept. of Comput. Sci., Southern California Univ., Los Angeles, CA ; Knoblock, C.A.

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 2D 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

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Pattern Recognition, 2006. ICPR 2006. 18th International Conference on  (Volume:2 )

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