Computer Processing of Line-Drawing Images
ACM Computing Surveys (CSUR)
Efficient error free chain coding of binary documents
DCC '95 Proceedings of the Conference on Data Compression
Linear-Time Construction of Optimal Context Trees
DCC '98 Proceedings of the Conference on Data Compression
DCC '02 Proceedings of the Data Compression Conference
An efficient chain code with Huffman coding
Pattern Recognition
A universal finite memory source
IEEE Transactions on Information Theory
Applications of universal context modeling to lossless compression of gray-scale images
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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We consider lossless compression of digital contours in map images. The problem is attacked by the use of context-based statistical modeling and entropy coding of chain codes. We propose to generate an optimal context tree by first constructing a complete tree up to a predefined depth, and then create the optimal tree by pruning out nodes that do not provide improvement in compression. Experiments show that the proposed method gives lower bit rates than the existing methods for the set of test images.