Study Of Palmprint And Face Recognition Algorithm

Face recognition and palmprint recognition has very large academic and practical values.A palmprint has much more information than a fingerprint. We can identify someone just utilize his pamlprint's character of line, point, texture and geometry. It's easy to accumulate a palmprint's information, and the cost of the sampling equipment is not higher. Theoretically, palmprint recognition should be more dependable and advanced than fingerprint recognition which was used more widely.In daily life, people knowing each other uses at most of person's face. Face is the most familiar model in human vision. The visual information reflected by face has important meaning and impact between people's intercommunication and intercourse. Because of its extensive and applied realm, face recognition technique has got the extensive concern with study in near three decades and become the most potential method of identity recognition.It is well known that every single bio characteristic has its own given drawbacks and it's very difficult to overcome them. Till now,there is not any single bio characteristic that could be used perfectly in practical application, and multi-bio characteristics fusion was used frequently to make the recognition have higher precision and dependability. In this paper, I've given an introduction of a new combining method of palmprint on the feature layer, and this method's main idea is that treating the right hand and the left hand's feature vectors as a complex vector's real part and imaginary part separately. Then, I list some experimental results and the analysis on them to prove that our method is good enough.As we known, LDA is a good method to perform the linear feature extraction. However, it often suffers from the small sample size problem when dealing with the high dimensional data. Moreover, while LDA is guaranteed to find the best directions when each class has a Gaussian density with a common covariance matrix, it can fail if the class densities are more general. In this paper, a new nonparametric linear feature extraction method, stepwise nonparametric...