An efficient 2D deformable objects detection and location algorithm

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摘要

This paper presents a complete method for the automatic detection and location of two-dimensional objects even in the presence of noise, occlusion, cluttering and/or deformations. This method is based on shape information extracted from the edges gradient and only needs a template of the object to be located. A new Generalized Hough Transform is proposed to automatically locate rigid objects in the presence of noise, occlusion and/or cluttering. A Bayesian scheme uses this rigid objects location algorithm to obtain the deformation of the object. The whole method is invariant to rotation, scale, displacement and minor deformations. Several examples with real images are presented to show the validity of the method.

论文关键词:Bayesian inference,Deformable templates,Generalized Hough transform,Invariant features,Object detection and location

论文评审过程:Received 23 August 2002, Accepted 29 April 2003, Available online 11 July 2003.

论文官网地址:https://doi.org/10.1016/S0031-3203(03)00168-7