원문정보
초록
영어
This paper presents an approach by various Algorithms stage by stage for Face Detection. It first detects the face portion, removing all other portion from an image. First it will remove the background and then the body or cloths portion of the image. To achieve this we propose an algorithm based on K-Mean clustering, Bresenham’s algorithm, Graham Scan Algorithm. With the help of image morphology, algorithm will detect the skin texture of the face. Image opening and closing will help to get the skin texture. Using a nose template algorithm will find the nose tip by template matching method. Feature vectors are calculated with respect to the nose tip as the origin of 8 octants. Image moment provides a measure for variation in the skin. This total process is done by the feature extraction algorithm.
목차
1. Introduction
2. Face Detection
2.1. Introduction to Face Detection
3. Proposed System
3.1. Background Removal Process
3.2. Creating Binary Image
3.3. Removing Cloths from Binary Image
3.4. Finding Concap Point and Removing Cloths
4. K – Mean Clustering
5. Applying Graham Scan Algorithm
6. Applying Bresenham's Algorithm
7. Conclusion
References