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.
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 (Presented at SPIE Defense + Security: April 12, 2017; Published: 1 May 2017); https://doi.org/10.1117/12.2262919.
Conference Presentations are recordings of oral presentations given at SPIE conferences and published as part of the conference proceedings. They include the speaker's narration along with a video recording of the presentation slides and animations. Many conference presentations also include full-text papers. Search and browse our growing collection of more than 12,000 conference presentations, including many plenary and keynote presentations.