Skin Segmentation based Elastic Bunch Graph Matching for efficient multiple Face Recognition

10/22/2013 ∙ by Sayantan Sarkar, et al. ∙ 0 ∙ share

This paper is aimed at developing and combining different algorithms for face detection and face recognition to generate an efficient mechanism that can detect and recognize the facial regions of input image. For the detection of face from complex region, skin segmentation isolates the face-like regions in a complex image and following operations of morphology and template matching rejects false matches to extract facial region. For the recognition of the face, the image database is now converted into a database of facial segments. Hence, implementing the technique of Elastic Bunch Graph matching (EBGM) after skin segmentation generates Face Bunch Graphs that acutely represents the features of an individual face enhances the quality of the training set. This increases the matching probability significantly.

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Skin Segmentation based Elastic Bunch Graph Matching for efficient multiple Face Recognition

Authors

Maximized Posteriori Attributes Selection from Facial Salient Landmarks for Face Recognition

ROI Segmentation for Feature Extraction from Human Facial Images

Agrupamento de Pixels para o Reconhecimento de Faces

Occlusion-guided compact template learning for ensemble deep network-based pose-invariant face recognition

Facial Keypoints Detection

Robotics Meets Cosmetic Dermatology: Development of a Novel Vision-Guided System for Skin Photo-Rejuvenation

Face Synthesis (FASY) System for Determining the Characteristics of a Face Image

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