The recognition of the persons from images has numerous applications in Image Surveillances and Computer Vision. Face detection in still images is applied in many of the devices and in many of the applications. Face detection in images is a recent technique which ensures the identification of person in the image. In a image normally the pose of the persons and the illumination variations were normally present. The main challenge of detecting face images in images is the pose and the illumination variations and sudden changes in the movement of the object. The images taken from cameras are taken. The surveillance images were normally not so clear and there may be some illumination variations and blurness at some places due to rapid movement of the objects. The proposed system analyzes and recognizes the exact face image from the image while the existing systems deals with the recognition of the face images from still images. The proposed system is capable of identifying the face images in the image in a better manner even though there are pose variations illumination variations and blurs occurring due to rapid motions of the subjects in the image. Individual recognition using Iris is most commonly employed in all the place. This requires some special cameras to take the Iris image and the obtained iris images were classified based on the features extracted. Only identification of person is not the application of Iris recognition. It can be developed to do many process. In this process the race of the person is identified. Also the input iris is fake or original is also identified. The iris image captured from the cameras were taken. Some Iris recognition system fails because some of the recognition systems identifies the iris image in photos, also some of the recognition systems identifies the fake iris images generated by some attackers. An iris recognition system that identifies the fake iris images are much needed. The proposed iris recognition system identifies the fake and original iris images. In order to identify fake and original iris image REISZ descriptors were derived from the input iris images. Before this process the iris image is preprocessed by resizing the iris image and then filtering the iris image using gaussian filter. The preprocessed iris image is then normalized. The normalization process identifies the iris and pupil region in the image correctly and it reshapes the identified positions. The normalization process improves the efficiency. The REISZ descriptors identifies the corner points in the iris image and then the extracted points were used to generate the codebook. The code book generation processes is done using Hierarchical Visual Code book generation method. The input iris image is then identified to be fake or original, Asian or Non-Asian using Support Vector Machine classifier. The eye pair is taken and the individuals are also recognized.