Rectangular decomposition of binary images

Authors:
Tom$#225;$#353; Suk;Cyril Höschl;Jan Flusser
Affiliations:
Institute of Information Theory and Automation of the ASCR, Praha 8, Czech Republic;Institute of Information Theory and Automation of the ASCR, Praha 8, Czech Republic;Institute of Information Theory and Automation of the ASCR, Praha 8, Czech Republic
Venue:
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
Year:
2012

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Abstract

The contribution deals with the most important methods for decomposition of binary images into union of rectangles. The overview includes run-length encoding and its generalization, decompositions based on quadtrees, on the distance transformation, and a theoretically optimal decomposition based on maximal matching in bipartite graphs. We experimentally test their performance in binary image compression and in convolution calculation and compare their computation times and success rates.