Title
Bit-Quad-Based Euler Number Computing
Abstract
The Euler number of a binary image is an important topological property for pattern recognition, image analysis, and computer vision. A famous method for computing the Euler number of a binary image is by counting certain patterns of bit-quads in the image, which has been improved by scanning three rows once to process two bit-quads simultaneously. This paper studies the bit-quad-based Euler number computing problem. We show that for a bit-quad-based Euler number computing algorithm, with the increase of the number of bit-quads being processed simultaneously, on the one hand, the average number of pixels to be checked for processing a bit-quad will decrease in theory, and on the other hand, the length of the codes for implementing the algorithm will increase, which will make the algorithm less efficient in practice. Experimental results on various types of images demonstrated that scanning five rows once and processing four bit-quads simultaneously is the optimal tradeoff, and that the optimal bit-quad-based Euler number computing algorithm is more efficient than other Euler number computing algorithms.
Year
DOI
Venue
2017
10.1587/transinf.2017EDP7012
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
Keywords
Field
DocType
Euler number, topological property, computer vision, pattern recognition, image analysis
Computer vision,Euler number,Algebra,Computer science,Artificial intelligence,Semi-implicit Euler method,Backward Euler method,Topological property
Journal
Volume
Issue
ISSN
E100D
9
1745-1361
Citations 
PageRank 
References 
0
0.34
7
Authors
5
Name
Order
Citations
PageRank
Bin Yao1314.84
Lifeng He244140.97
shiying kang311.39
Xiao Zhao4477.99
Yuyan Chao531524.07