Name
Abstract | ||
|---|---|---|
Human Face Recognition has become a potential method of biometric authentication because of its most non-intrusive and user-friendly nature. Automatic face recognition poses various challenges due to: (a) inherent variability of face due to age, gender and race; (b) different facial expressions and orientations of same person's face; and (c) images containing faces have high degree of variability in size, texture, background and illumination. The proposed model uses a two pass method in which the input image is first processed using conventional image processing filters to enhance it and then the edges are detected in the image using convolution mask; which is further followed by face recognition using neural network. This helps the model to achieve more accuracy and the whole process to be more efficient than simply applying neural network model for face recognition. |
Year | Venue | Keywords |
|---|---|---|
2006 | IC-AI | face recognition,classification,convolution filters.,— neural network,image processing,facial expression,neural network model,neural network,biometric authentication |
Field | DocType | Citations |
Neocognitron,Computer vision,Facial recognition system,Three-dimensional face recognition,Pattern recognition,Computer science,Convolution,Image processing,Time delay neural network,Artificial intelligence,Biometrics,Artificial neural network | Conference | 0 |
PageRank | References | Authors |
0.34 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| V. Rihani | 1 | 2 | 2.72 |
| Amit Bhandari | 2 | 0 | 0.34 |
| C. P. Singh | 3 | 0 | 0.34 |