The efficiency, quality and accuracy of facial image recognition are restricted by luminance, posture, image quality, massive data and method of image recognition, etc. In response to this, this thesis proposes a facial image recognition algorithm based on BP neural network. It improves on traditional BP neutral network by constructing neutrons of facial image recognition in the input layer, hidden layer and output layer. And by constructing the network framework structure of facial image recognition, it also constructs design elements of facial image recognition from input code and output code and therefore constructs the facial image recognition algorithm based on BP neural network. This thesis verifies the algorithm through practical cases and proves that the algorithm is effective and operable.
목차
Abstract 1. Introduction 2. Basic Concepts of BP Neural Network 2.1. Neural Model 2.2. BP Network Model 3. The Facial Image Recognition Algorithm Based on BP Neural Network 3.1. Input Code of Facial Image Recognition 3.2. Output Code of Facial Image Recognition 3.3. Network Structure of Facial Image Recognition 3.4. Facial Image Recognition Algorithm Based on BP and Operation Steps 4. Algorithm Validation and Analysis 5. Conclusions References
보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Signal Processing, Image Processing and Pattern Recognition
간기
격월간
pISSN
2005-4254
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.9 No.4