A robust HOG-based descriptor for pattern recognition

被引：3
作者：
Diaz-Escobar, Julia [1 ]
Kober, Vitaly [1 ,2 ]
机构：
[1] CICESE, Dept Comp Sci, Ensenada 22860, Baja California, Mexico
[2] Chelyabinsk State Univ, Dept Math, Chelyabinsk, Russia
来源：
APPLICATIONS OF DIGITAL IMAGE PROCESSING XXXIX | 2016年 / 9971卷
基金：
俄罗斯科学基金会;
关键词：
Pattern recognition; phase-congruency; nonuniform illumination; PHASE; VISION;
D O I：
10.1117/12.2237963
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
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页数：7
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