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

Christina D. Schrider; Julie A. Skipper; Daniel W. Repperger

doi:10.1117/12.703651

27 February 2007 Histogram-based template matching for object detection in images with varying contrast

Christina D. Schrider, Julie A. Skipper, Daniel W. Repperger

Proceedings Volume 6497, Image Processing: Algorithms and Systems V; 64970B (2007) https://doi.org/10.1117/12.703651
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States

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.

Citation Download Citation

Christina D. Schrider, Julie A. Skipper, and Daniel W. Repperger "Histogram-based template matching for object detection in images with varying contrast", Proc. SPIE 6497, Image Processing: Algorithms and Systems V, 64970B (27 February 2007); https://doi.org/10.1117/12.703651

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