Exploring Image Unified Space for Improving Information Technology for Person Identification

This paper describes the study of conditions and parameter settings of the algorithm, that underlies in the basis of information technology of person recognition and identification, for creating a unified space for both low-quality and high-quality images with the purpose of developing the requirements to the input images, that will allow correctly identify images with different characteristics. For experimental research the algorithm was used that underlies in information technology of person identification in video stream. It includes the anisotropic diffusion as an image preprocessing method, Gabor wavelet transform as an image processing method, histogram of oriented gradients (HOG) and local binary patterns in 1-dimensional space (1DLBP) as the methods of feature vector extraction from the images. In this work anisotropic diffusion was applied with the parameter that preserves sharper boundaries than previous formulations and improves the automatic stopping of the diffusion. In the study three person images databases were used: The Database of Faces, Facial Recognition Technology (FERET) database and Surveillance Cameras Face Database (SCface). The algorithm performance provided various identification accuracy rate results with the difference, which amount to 20% in average. It arose the issue of input images space mismatching that significantly affected the algorithm performance. Therefore, it has been decided to perform the experimental research to search the possibility to create unified space of the requirements to the input images that will allow correctly identify images from different databases. So, there were performed the experiments with the image compression variety, difference of image resolutions and areas of face regions covering the images.