A crypto-marking method for secure vector map

Multimedia Tools and Applications - A crypto-marking technique can be used to provide a solution to the secure transmission and storage of highly valuable and detailed vector maps. Such a solution...     

Reversible DNA data hiding using multiple difference expansions for DNA authentication and storage

Multimedia Tools and Applications - Recently the data hiding techniques on DNA sequence have attracted interest for DNA authentication and high-capacity DNA storage. However, since DNA sequence...     

A hybrid method based on dynamic compensatory fuzzy neural network algorithm for face recognition

Human face recognition skills can make simultaneous use of a variety of information from the face, including information about the age, sex, race, identity, and even current mood of the person. In this paper, a hybrid method combined Eigenface-LDA with Dynamic Compensatory Fuzzy Neural Network (DCFNN) is proposed for face recognition. Eigenfaces-LDA algorithm is used for face image of dimensionality reduction and finding a best subspace for classification, the extracted feature will be considered as the input of DCFNN. An improved Dynamic Fuzzy Neural Network is proposed by combing Dynamic Fuzzy Neural Network and Compensatory Fuzzy Neural Network to solve the problem of feature classification. The proposed method has been tested on ORL and Yale face database; the experimental results show that our method can reduce the dimension of facial features well and recognize faces that under different illumination, pose and expression accurately.