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Proceedings Paper

Histogram-based template matching for object detection in images with varying contrast
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Paper Abstract

Our challenge was to develop a semi-automatic target detection algorithm to aid human operators in locating potential targets within images. In contrast to currently available methods, our approach is relatively insensitive to image brightness, image contrast and object orientation. Working on overlapping image blocks, we used a sliding difference method of histogram matching. Incrementally sliding the histograms of the known object template and the image region of interest (ROI) together, the sum of absolute histogram differences was calculated. The minimum of the resultant array was stored in the corresponding spatial position of response surface matrix. Local minima of the response surface suggest possible target locations. Because the template contrast will rarely perfectly match the contrast of the actual image contrast, which can be compromised by illumination conditions, background features, cloud cover, etc., we perform a random contrast manipulation, which we term 'wobble', on the template histogram. Our results have shown increased object detection with the combination of the sliding histogram difference and wobble.

Paper Details

Date Published: 27 February 2007
PDF: 8 pages
Proc. SPIE 6497, Image Processing: Algorithms and Systems V, 64970B (27 February 2007); doi: 10.1117/12.703651
Show Author Affiliations
Christina D. Schrider, Wright State Univ. (United States)
Julie A. Skipper, Wright State Univ. (United States)
Daniel W. Repperger, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 6497:
Image Processing: Algorithms and Systems V
Jaakko T. Astola; Karen O. Egiazarian; Edward R. Dougherty, Editor(s)

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