A comparison study of image descriptors on low-resolution face image verification

Face images are commonly used in various tasks such as face detection, facial feature extraction, and face recognition. In the security applications, the images are used as input of the identification or verification systems due to its usability, availability, and reliability. Since the capacity of memory of face database system is limited, all images retained in the database should be of small size or low resolution. This paper proposes low-resolution face image verification based on image similarity measure as well as five image descriptors-Color Histograms, Auto Correlograms, MPEG7-EHD, CEDD, and Tamura´s Texture. The results of image comparison were depicted under five image types: regular image, overexposed image, underexposed image, non-frontal image, image with facial expression. Lastly, the discussion of our results was provided to present the relationship between the descriptors and the conditions. With our comparison study, the results showed that for a low resolution image the important factors of image are edge, color and gradient. This information can be used in the further various studies.