An Approach to Face Recognition of 2-D Images Using Eigen Faces and PCA
Annapurna Mishra · Signal & Image Processing An International Journal · 2012
Face detection is to find any face in a given image.Face recognition is a two-dimension problem used for detecting faces.The information contained in a face can be analysed automatically by this system like identity, gender, expression, age, race and pose.Normally face detection is done for a single image but it can also be extended for video stream.As the face images are normally upright, they can be described by a small set of 2-D characteristics views.Here the face images are projected to a feature space or face space to encode the variation between the known face images.The projected feature space or the face space can be defined as 'eigenfaces' and can be formed by eigenvectors of the face image set.The above process can be used to recognize a new face in unsupervised manner.This paper introduces an algorithm which is used for effective face recognition.It takes into consideration not only the face extraction but also the mathematical calculations which enable us to bring the image into a simple and technical form.It can also be implemented in real-time using data acquisition hardware and software interface with the face recognition systems.Face recognition can be applied to various domains including security systems, personal identification, image and film processing and human computer interaction.