원문정보
초록
영어
The objective of this paper is to propose a new algorithm in face detection that has the capabilities of detecting the face with different poses and under different conditions. This objective is obtained in different stages and using different proposed algorithms. Firstly, a robust segmentation algorithm is proposed to extract and segment the skin region from the image. Secondly, different filtering steps are applied to this segmented image to obtain the face candidate region only. After that, Feature-Based approach is used to detect the features from this candidate face which can work in real-time with minimal training in contrast to other approaches such as image-based approach. Finally, some rules is applied in order to judge if this candidate is profile face or not either the profile face is right or left. Experimental results show that the proposed method is robust under a wide range of lighting conditions, different poses and different races. These results are taken from three different face databases. The proposed method is implemented using Matlab version 7.6 software and gives a correct detection rate reach 90 %.
목차
1. Introduction
2. Learning Skin Color Model Parameters
3. Proposed Skin Segmentation
3.1 Image Filtering
4. Face Feature Searching
4.1 Nose Point
4.2 Chin Point
4.3 Nose Bottom Point
4.4 Nose Above Point
4.5 Neck Point
4.6 Angle Between (Nose, Nose Above and Nose Bottom) Points
5. The Proposed Feature-Based FD Algorithm
6. Results and Discussion
6.1 Segmentation Process
6.2 Proposed Face Detection Algorithm Evaluation Results
6.3 Discussion and Comparison
6.4 Case Of Failure
7. Conclusion
References