A hybrid face detection system using combination of appearance-based and feature-based methods

Human face detection is preliminary required step of face recognition systems as well as a very important task in many applications, such as security access control systems, video surveillance, human computer interface and image database management. This paper intends to combine Viola and Jones face detection method with a color-based method to propose an improved face detection method. Experimental results show that our method efficiently decreased false positive rate and subsequently increased accuracy of the face detection system especially in complex background images. Also our proposed method considerably increased face detection speed

Image databases: Problems and perspectives

With the increasing number of computer graphics, image processing, and pattern recognition applications, economical storage, efficient representation and manipulation, and powerful and flexible query languages for retrieval of image data are of paramount importance. These and related issues pertinent to image data bases are examined

Human Face Recognition and Detection

Human face detection and recognition play important roles in many applications such as video surveillance and face image database management. In our project, we have studied worked on both face recognition and detection techniques and developed algorithms for them. In face recognition the algorithm used is PCA (principal component analysis), MPCA(Multilinear Principal Component Analysis) and LDA(Linear Discriminant Analysis) in which we recognize an unknown test image by comparing it with the known training images stored in the database as well as give information regarding the person recognized. These techniques works well under robust conditions like complex background, different face positions. These algorithms give different rates of accuracy under different conditions as experimentally observed. In face detection, we have developed an algorithm that can detect human faces from an image. We have taken skin colour as a tool for detection. This technique works well for Indian faces which have a specific complexion varying under certain range. We have taken real life examples and simulated the algorithms in MATLAB successfully

Storage capacity of holographic associative memories

The storage capacity of holographic associative memories is estimated. An argument based on the available degrees of freedom shows that the number of patterns that can be stored is limited by the space-bandwidth product of the hologram divided by the number of pixels in each pattern. A statistical calculation shows that if we attempt to store associations by multiply exposing the hologram, the cross talk among the stored items severely degrades the output fidelity. This confirms the storage capacity predicted by the degrees-of-freedom argument

Solution of large linear systems of equations on the massively parallel processor

The Massively Parallel Processor (MPP) was designed as a special machine for specific applications in image processing. As a parallel machine, with a large number of processors that can be reconfigured in different combinations it is also applicable to other problems that require a large number of processors. The solution of linear systems of equations on the MPP is investigated. The solution times achieved are compared to those obtained with a serial machine and the performance of the MPP is discussed