Cited By
View all- Tavakoli AFarazmanesh D(2019)Unifying the skeletonization methods via modifying imagesPattern Analysis & Applications10.1007/s10044-018-0751-y22:3(919-933)Online publication date: 31-Jul-2019
Morphological Decomposition and Compression of Binary Images via a Minimum Set Cover Algorithm
Pages 71 - 83
Abstract
In this paper, by a novel morphological decomposition method, we propose an efficient compression approach. Our presented decomposition arises from solving a minimum set cover problem (MSCP) obtained from the image skeleton data. We first use the skeleton pixels to create a collection of blocks which cover the foreground. The given blocks are both overlapped and too many. Hence, in order to find the minimum number of the blocks that cover the foreground, we form an MCSP. To solve this problem, we present a new algorithm of which accuracy is better than those of the known methods in the literatures. Also, its error analysis is studied to obtain an error bound. In the sequel, we present a fast algorithm which include an extra parameter by which the relation between the accuracy and CPU time can be controlled. Finally, several examples are given to confirm the efficiency of our approach.
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Published: 01 January 2019
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View all- Tavakoli AFarazmanesh D(2019)Unifying the skeletonization methods via modifying imagesPattern Analysis & Applications10.1007/s10044-018-0751-y22:3(919-933)Online publication date: 31-Jul-2019
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