ATR algorithm performance evaluation based on the simulation image and real image

Lamei Zou; Zhiguo Cao; Weidong Yang

doi:10.1117/12.2031395

27 October 2013 ATR algorithm performance evaluation based on the simulation image and real image

Lamei Zou, Zhiguo Cao, Weidong Yang

Proceedings Volume 8919, MIPPR 2013: Pattern Recognition and Computer Vision; 89190T (2013) https://doi.org/10.1117/12.2031395
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

Abstract

Currently there is no algorithm which can be adapted to all of the imaging conditions. So, it is necessary for us to find a method to evaluate the existing ATR (automatic target recognition) algorithm. We do some researches on ATR algorithm performance evaluation based on test methodology. The basic idea of the algorithm performance evaluation is to establish the relationship model between the image quality characteristics and the algorithm’s performance. In this paper, the algorithm performance evaluation’s techniques are studied, which include the algorithm performance assessment framework, the universal test image database’s creating, and the research of the image quality evaluation model. Firstly, under the guidance of the orthogonal experimental design method, we construct a universal test image database which includes the simulation image and the outfield flight data. And then this paper propose a method to establish the relation model between image quality characteristic and ATR algorithm based on SVM classifier. Finally we use the model to evaluate algorithm’s performance. We conduct experiments on the matching algorithm’s performance evaluation. The experimental results show that the proposed evaluation framework is efficient and the evaluation model is well.

Citation Download Citation

Lamei Zou, Zhiguo Cao, and Weidong Yang "ATR algorithm performance evaluation based on the simulation image and real image", Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 89190T (27 October 2013); https://doi.org/10.1117/12.2031395

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