Shape Matching Based on Rectangularized Curvature Scale-Space Maps

Author(s):  
Wen Zhou ◽  
Baojiang Zhong ◽  
Kai-Kuang Ma
Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 499 ◽  
Author(s):  
Chaoyan Zhang ◽  
Yan Zheng ◽  
Baolong Guo ◽  
Cheng Li ◽  
Nannan Liao

Shape classification and matching is an important branch of computer vision. It is widely used in image retrieval and target tracking. Shape context method, curvature scale space (CSS) operator and its improvement have been the main algorithms of shape matching and classification. The shape classification network (SCN) algorithm is proposed inspired by LeNet5 basic network structure. Then, the network structure of SCN is introduced and analyzed in detail, and the specific parameters of the network structure are explained. In the experimental part, SCN is used to perform classification tasks on three shape datasets, and the advantages and limitations of our algorithm are analyzed in detail according to the experimental results. SCN performs better than many traditional shape classification algorithms. Accordingly, a practical example is given to show that SCN can save computing resources.


Author(s):  
KIMCHENG KITH ◽  
BAREND J. VAN WYK ◽  
MICHAËL A. VAN WYK

In many image analysis applications, such as image retrieval, the shape of an object is of primary importance. In this paper, a new shape descriptor, namely the Normalized Wavelet Descriptor (NWD), which is a generalization and extension of the Wavelet Descriptor (WD), is introduced. The NWD is compared to the Fourier Descriptor (FD), which in image retrieval experiments conducted by Zhang and Lu, outperformed even the Curvature Scale Space Descriptor (CSSD). Image retrieval experiments have been conducted using a dataset containing 2D-contours of 1400 objects extracted from the standard MPEG7 database. For the chosen dataset, our experimental results show that the NWD outperforms the FD.


2007 ◽  
Vol 28 (5) ◽  
pp. 545-554 ◽  
Author(s):  
Xiaohong Zhang ◽  
Ming Lei ◽  
Dan Yang ◽  
Yuzhu Wang ◽  
Litao Ma

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