| Citation: | LU Yongqiang, LI Zhiyang, CHEN Yinan, et al. Two-dimensional shape recognition based on contour and skeleton sequence coding[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(12): 2523-2532. doi: 10.13700/j.bh.1001-5965.2019.0376(in Chinese)
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Two-dimensional shape recognition is a fundamental problem in object recognition, which is widely used in trademark retrieval, fingerprint recognition, object location, image retrieval and other fields. Recently, two-dimensional shape recognition based on bioinformatics has become a new research direction, whose basic idea is to transform the contour of a planar shape into a biological information sequence. The two-dimensional shape matching and recognition are then achieved by the standard alignment tools of such biological information sequence. However, the classic coding method still suffers from the problems of code redundancy and low accuracy. In this paper, we present a new coding method based on both the shape contour and skeleton sequence. Firstly, skeletons are used to represent slender branches of the shape to reduce coding redundancy. Secondly, the contour and skeleton are coded in different ways to compact the code and improve the matching accuracy. Finally, extensive shape recognition experiments are conducted on three public datasets and the proposed method is compared with a variety of shape recognition methods. The experimental results demonstrate that the proposed method has achieved higher performance in several experiments, and the recognition accuracy rate is improved by nearly 5% compared with basic shape feature description methods.
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