FACE RECOGNITION USING EIGEN VECTORS
In this project we will make the program to identify the face or any image using MATLAB. In this there will be photographs in our database. Software will check the photo graph we want to check is in database or not. If not then it will display image is not in database. If yes then it will display , image is available in database. Previous mathematicians have theorized that certain cognitive processes, such as face recognition, can be emulated through the use of principal component analysis. we have attempted to use techniques of principal component analysis, more specifically, eigen-vector analysis, to develop a computer program capable of face recognition. Specifically, the goal of our project was to investigate a mathematical basis and model for face recognition using principal component analysis with eigenvectors, and then implement a working model in the form of a computer program.
The fundamental idea behind principal component analysis with eigenvectors has its basis in linear algebra. Put simply, if there are a series of multi-dimensional vectors representing objects which have similarities, it is possible to use a transformation matrix and eigenvectors to orient a space which requires fewer dimensions to accurately describe these multidimensional vectors. For instance, if in three dimensional space, there was a cloud of particles that lied in a two dimensional plane skewed from the axes (Fig 1), it would be possible to orient a new space with a new origin and new unit vectors such that the cloud which previously required a three dimensional representation could now easily be represented in only two dimensions.