A novel rotation/scale invariant template matching algorithm using weighted adaptive lifting scheme transform

作者:

Highlights:

摘要

This paper presents a novel algorithm for detecting user-selected objects in given test images based on a new adaptive lifting scheme transform. Given an object as a template, we first select a set of coefficients as object features in the wavelet transform domain and then build an adaptive transform based on the selected features. The goal of the new adaptive transform is to vanish the selected features in the transform domain. After applying both non-adaptive and adaptive transforms to a given test image, the corresponding transform domain coefficients are compared for detecting the object of interest. In addition, the proposed detection algorithm is combined with the proper log-polar mapping model in the parametric template space to attain rotation/scale invariance property. Finally, we have verified the properties of our proposed algorithm with experimental results.

论文关键词:Adaptive lifting scheme,Object detection,Rotation/scale invariant template matching

论文评审过程:Received 6 December 2008, Revised 18 September 2009, Accepted 22 December 2009, Available online 11 February 2010.

论文官网地址:https://doi.org/10.1016/j.patcog.2009.12.014