Title
Shape Matching Based on Multi-Scale Invariant Features
Abstract
Shape matching has been extensively used in various fields. The local feature-based or global feature-based algorithms can hardly describe the shape comprehensively due to their inherent defects. Combining the local and global feature to describe the shape has become a trend. In this paper, an improved discrete curve evolution algorithm is proposed which combines the discrete curve evolution with the uniform sampling and achieves a better description of the shape contour. Three simple and intuitive multi-scale features which represent both the global and local features of shapes are designed from aspects of the spatial relationship of contour points, structural information of contour sequence, and shape geometry feature. A cyclic Smith-Waterman algorithm is introduced to solve local contour matching and starting point selection. Experimental results demonstrate that our proposed features are translation, rotation, and scaling invariant, and have good robustness to deformation. Retrieval accuracies of Kimia99, Kimai216, and MPEG-7 indicate that our method can bring out a better performance.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2935879
IEEE ACCESS
Keywords
DocType
Volume
Shape matching,improved discrete curve evolution,multi-scale invariant features,cyclic Smith-Waterman algorithm
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Kun Zhang14724.15
Ma Xiao200.34
Li Xinguo300.34