Earticle

초록

영어

A face recognition algorithm based on local binary Haar feathers which represented as Kadane optimizing multi-threshold AdaBoost was proposed according to the problems of texture shape feature representation and classification algorithm accuracy in the process of facial classifying detection and recognition, First, improve the traditional expression by using image Local binary pattern of Haar features , improve image model of texture and shape feature expression ability ; Secondly, for single threshold weak learning algorithm we can not make full use of local binary Haar feature information, resulting in a lower classification accuracy problem proposed Kadane optimizing multi-threshold AdaBoost classifier, to achieve local binary Haar feature representation of facial high accuracy recognition; Finally, through the experiments show, efficient face recognition rate can reach more than 90% by the algorithm,which is superior to the selected comparison algorithm.

목차

Abstract
 1. Introduction
 2. Facial Haar Feature Local Binary Pattern
  2.1. LBP Feature Extraction
  2.2. Haar Features
  2.3. HLBP Features
 3. Single Threshold Weak Classifier Cascade Face Detection
  3.1. Gentle AdaBoost Learning
  3.2. Optimal Threshold Determination
 4. Multi-Threshold Weak Classifier
  4.1. Kadane Calculation of Threshold
  4.2. Multi-Threshold Weak Classifier
 5. Experimental Analysis
 6. Conclusion
 References

키워드

저자

• Yu Xiang [ Department of Information Technology, Tianjin Chengjian University, Tianjin City, China ]

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