Paper
26 August 2011 A method for real-time implementation of HOG feature extraction
Hai-bo Luo, Xin-rong Yu, Hong-mei Liu, Qing-hai Ding
Author Affiliations +
Abstract
Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hai-bo Luo, Xin-rong Yu, Hong-mei Liu, and Qing-hai Ding "A method for real-time implementation of HOG feature extraction", Proc. SPIE 8193, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, 819302 (26 August 2011); https://doi.org/10.1117/12.901081
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Feature extraction

Target detection

Automatic target recognition

Target recognition

Computer vision technology

Field programmable gate arrays

Machine vision

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