Earticle

초록

영어

Feature extraction methods of image directly affect the feature recognition results based on computer vision-based gesture recognition. This paper proposed a gesture feature extraction method of hexagonal structure, which is based on histograms of oriented gradients. This paper transforms the quadrilateral structure into hexagonal structure of the image and defines hexagonal block structure. Using different structures, different sizes of hexagonal blocks extract gesture feature and recognize on different sizes image. Experimental results show that hexagonal structure block is more appropriate than conventional histograms of oriented gradients structure block, the hexagonal structure histograms of oriented gradients feature extraction method is more efficient than the square and circular structure histograms of oriented gradients feature, using gentle_adaboost classifier achieved higher recognition rate.

목차

Abstract
 1. Introduction
 2. Summary of the Related Works
 3. Hexagonal Structure Histograms of Oriented Gradients
  3.1 Histograms of Oriented Gradients
  3.2 Virtual Hexagonal Structure
  3.3 Extracting H-HOG Features
 4. Experiments and Results
  4.1 Acquiring and Preprocessing Gesture Images
  4.2 Designing Experimental and Analyzing Results
 5. Conclusion
 Acknowledgments
 References

키워드

저자

• Pang Haibo [ School of Software Technology, Zhengzhou University, Zhengzhou, China, 450002 ]
• Liu Chengming [ School of Software Technology, Zhengzhou University, Zhengzhou, China, 450002 ]
• Zhao Zhe [ School of Software Technology, Zhengzhou University, Zhengzhou, China, 450002 ]
• Zhang Shuyan [ School of Software Technology, Zhengzhou University, Zhengzhou, China, 450002 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605