원문정보
보안공학연구지원센터(IJMUE)
International Journal of Multimedia and Ubiquitous Engineering
Vol.10 No.4
2015.04
pp.311-324
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Bezier curve are very strong for variety of application. Specifically in image processing it applies to object recognition, face recognition, and human gait recognition. It also works on fingerprint and other biometric system recognition. This paper presents a work to recognize digital images of human frontal faces using the approximated Bezier curve and an intelligent process of learning using neural network. The main structural features of faces like eye, eyebrows, nose, lips, and Face boundaries are extracted and using minimum of these features face is recognized efficiently.
목차
Abstract
1. Introduction
1.1 Overview of Bezier Curve
1.2 Overview of Neural Network as Classifier
2. The Framework of Proposed System
3. Results and Performance Analysis
3.1. Image Acquisition
3.2. Face Detection
3.3 Image Pre-processing
3.4 Canny Edge Detection and Harris Corner Detection
3.5 Training Data of Neural Network
4. Conclusion
References
1. Introduction
1.1 Overview of Bezier Curve
1.2 Overview of Neural Network as Classifier
2. The Framework of Proposed System
3. Results and Performance Analysis
3.1. Image Acquisition
3.2. Face Detection
3.3 Image Pre-processing
3.4 Canny Edge Detection and Harris Corner Detection
3.5 Training Data of Neural Network
4. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보