27-05-2011, 09:31 PM
Face Recognition using Neural Networks
The face recognition is performed by using the main features of the face to identify the given face. It is a major biometric method. here, a neural based algorithm is used to detect the frontal views of the faces. A Principal component analysis (PCA) is used to reduce the dimensionality of the face. Back propagation Neural Network (BPNN) is used in the detection of the face. For the performance metrics, about 200 faces are taken from the yale database and the Acceptance ratio and Execution time are calculated for the database for comparison. The results show that the neural based face recognition algorithms are very efficient with an acceptance ratio of 90%. Usually a face recognition system identifies a human face from database images automatically. Nowadays the digital cameras implement a face detection feature. all the possible appearance variations caused by facial features, occlusions, change in illumination etc. must be taken into account. a Neural and PCA based algorithm for efficient and robust face recognition is discussed in this article.
[attachment=13966]
The face recognition is performed by using the main features of the face to identify the given face. It is a major biometric method. here, a neural based algorithm is used to detect the frontal views of the faces. A Principal component analysis (PCA) is used to reduce the dimensionality of the face. Back propagation Neural Network (BPNN) is used in the detection of the face. For the performance metrics, about 200 faces are taken from the yale database and the Acceptance ratio and Execution time are calculated for the database for comparison. The results show that the neural based face recognition algorithms are very efficient with an acceptance ratio of 90%. Usually a face recognition system identifies a human face from database images automatically. Nowadays the digital cameras implement a face detection feature. all the possible appearance variations caused by facial features, occlusions, change in illumination etc. must be taken into account. a Neural and PCA based algorithm for efficient and robust face recognition is discussed in this article.
[attachment=13966]
