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Proceedings Paper

Building recognition based on big template in FLIR images
Author(s): Jiangwei Zhang; Zhaodong Niu; Songlin Liu; Fang Liu; Zengping Chen
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Paper Abstract

In order to enhance the robustness of building recognition in forward-looking infrared (FLIR) images, an effective method based on big template is proposed. Big template is a set of small templates which contains a great amount of information of surface features. Its information content cannot be matched by any small template and it has advantages in conquering noise interference or incompleteness and avoiding erroneous judgments. Firstly, digital surface model (DSM) was utilized to make big template, distance transformation was operated on the big template, and region of interest (ROI) was extracted by the way of template matching between the big template and contour of real-time image. Secondly, corners were detected from the big template, response function was defined by utilizing gradients and phases of corners and their neighborhoods, a kind of similarity measure was designed based on the response function and overlap ratio, then the template and real-time image were matched accurately. Finally, a large number of image data was used to test the performance of the algorithm, and optimal parameters selection criterion was designed. Test results indicate that the target matching ratio of the algorithm can reach 95%, it has effectively solved the problem of building recognition under the conditions of noise disturbance, incompleteness or the target is not in view.

Paper Details

Date Published: 23 October 2014
PDF: 9 pages
Proc. SPIE 9244, Image and Signal Processing for Remote Sensing XX, 92441T (23 October 2014); doi: 10.1117/12.2066634
Show Author Affiliations
Jiangwei Zhang, National Univ. of Defense Technology (China)
Zhaodong Niu, National Univ. of Defense Technology (China)
Songlin Liu, National Univ. of Defense Technology (China)
Fang Liu, National Univ. of Defense Technology (China)
Zengping Chen, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 9244:
Image and Signal Processing for Remote Sensing XX
Lorenzo Bruzzone, Editor(s)

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