Improved maximum average correlation height filter with adaptive log base selection for object recognition

Sara Tehsin; Saad Rehman; Ahmad Bilal Awan; Qaiser Chaudry; Muhammad Abbas; Rupert Young; Afia Asif

doi:10.1117/12.2223621

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20 April 2016 Improved maximum average correlation height filter with adaptive log base selection for object recognition

Sara Tehsin, Saad Rehman, Ahmad Bilal Awan, Qaiser Chaudry, Muhammad Abbas, Rupert Young, Afia Asif

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Proceedings Volume 9845, Optical Pattern Recognition XXVII; 984506 (2016) https://doi.org/10.1117/12.2223621
Event: SPIE Defense + Security, 2016, Baltimore, Maryland, United States

Abstract

Sensitivity to the variations in the reference image is a major concern when recognizing target objects. A combinational framework of correlation filters and logarithmic transformation has been previously reported to resolve this issue alongside catering for scale and rotation changes of the object in the presence of distortion and noise. In this paper, we have extended the work to include the influence of different logarithmic bases on the resultant correlation plane. The meaningful changes in correlation parameters along with contraction/expansion in the correlation plane peak have been identified under different scenarios. Based on our research, we propose some specific log bases to be used in logarithmically transformed correlation filters for achieving suitable tolerance to different variations. The study is based upon testing a range of logarithmic bases for different situations and finding an optimal logarithmic base for each particular set of distortions. Our results show improved correlation and target detection accuracies.

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Sara Tehsin, Saad Rehman, Ahmad Bilal Awan, Qaiser Chaudry, Muhammad Abbas, Rupert Young, and Afia Asif "Improved maximum average correlation height filter with adaptive log base selection for object recognition", Proc. SPIE 9845, Optical Pattern Recognition XXVII, 984506 (20 April 2016); https://doi.org/10.1117/12.2223621

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