Combined with the characteristics of the forward-looking template matching algorithm, this paper proposed an evaluation method for ATR algorithm based on decision tree. The image features of the simulated real-time images and the template images are extracted as the input attribute, and the recognition results of the real-time images are used as the label. The input attribute and the label make up the training samples, and a series of decision trees are generated through the CART algorithm. As the real-time image of the target area is difficult to obtain, the image features of the simulated real-time images of the target area are extracted, and then the recognition results and their confidence level are predicted by using different decision trees corresponding to different ATR algorithms. The ATR algorithms are evaluated by comparing the prediction results and their confidence level.

Date Published: 29 August 2016
PDF: 5 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100330B (29 August 2016); doi: 10.1117/12.2245189

Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)