Compressed imagery detection rate through map seeking circuit, and histogram of oriented gradient pattern recognition

Kathy A. Newtson; Charles C. Creusere

doi:10.1117/12.2262919

1 May 2017 Compressed imagery detection rate through map seeking circuit, and histogram of oriented gradient pattern recognition

Kathy A. Newtson, Charles C. Creusere

Author Affiliations +

Proceedings Volume 10203, Pattern Recognition and Tracking XXVIII; 102030F (2017) https://doi.org/10.1117/12.2262919
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

This research investigates the features retained after image compression for automatic pattern recognition purposes. Many raw images with vehicles in them were collected for these experiments. These raw images were significantly compressed using open-source JPEG and JPEG2000 compression algorithms. The original and compressed images are processed with a Map Seeking Circuit (MSC) pattern recognition algorithm, as well as a Histogram of Oriented Gradient (HOG) with Support Vector Machine (SVM) pattern recognition program. Detection rates are given for these images that demonstrates the feature extraction capabilities as well as false alarm rates when the compression was increased. JPEG2000 compression results show preservation of the features needed for automatic pattern recognition which was better than the JPEG standard image compression results.

Conference Presentation

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Kathy A. Newtson and Charles C. Creusere "Compressed imagery detection rate through map seeking circuit, and histogram of oriented gradient pattern recognition", Proc. SPIE 10203, Pattern Recognition and Tracking XXVIII, 102030F (1 May 2017); https://doi.org/10.1117/12.2262919

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