Abstract: The face recognition is an application which is used for identifying or verifying a person from a digital image. The common problem that often occurs while identifying the face from image is due to the low resolution in images especially when it is captured from a long distance. In automated face recognition system, this has always been a challeging problem. To overcome this problem, an approach to learn relationship between the high resolution space and the VLR image space for face is proposed. In this new approach the face recognition applications under the VLR problem is designed for good visuality. To create the Very Low Resolution (VLR) image corresponding to each of these High Resolution (HR) images, the HR images are resized to 64x48 pixels. The Very Low Resolution (VLR) of the face image is <16x12 pixels. The proposed system is implemented in MATLAB. The performance of the proposed system is tested. The proposed system is highly accurate and extremely fast in processing the image data. Experimental results show that proposed method outperforms existing methods. The VLR face recognition problem has been defined and discussed in this study. For good visual quality applications, a new data constraint that measures the error in the HR image space was developed and RLSR was proposed.
C. Senthil Singh and M. Manikandan, 2014. Face Recognition Using Relationship Learning Based Super Resolution Algorithm. Asian Journal of Information Technology, 13: 175-181.