A robust HOG-based descriptor for pattern recognition

Julia Diaz-Escobar; Vitaly Kober

doi:10.1117/12.2237963

27 September 2016 A robust HOG-based descriptor for pattern recognition

Julia Diaz-Escobar, Vitaly Kober

Proceedings Volume 9971, Applications of Digital Image Processing XXXIX; 99712A (2016) https://doi.org/10.1117/12.2237963
Event: SPIE Optical Engineering + Applications, 2016, San Diego, California, United States

Abstract

The Histogram of Oriented Gradients (HOG) is a popular feature descriptor used in computer vision and image processing. The technique counts occurrences of gradient orientation in localized portions of an image. The descriptor is sensible to the presence in images of noise, nonuniform illumination, and low contrast. In this work, we propose a robust HOG-based descriptor using the local energy model and phase congruency approach. Computer simulation results are presented for recognition of objects in images affected by additive noise, nonuniform illumination, and geometric distortions using the proposed and conventional HOG descriptors.

Citation Download Citation

Julia Diaz-Escobar and Vitaly Kober "A robust HOG-based descriptor for pattern recognition", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99712A (27 September 2016); https://doi.org/10.1117/12.2237963

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