Low-Resolution Face Recognition(LRFR) System: A Review

Over the last few years, low-resolution face recognition (LRFR) has received a lot of attention. This kind of system comes into assistance in the recognition of the correct identity of a person whose image is taken in low resolution but whose image is stored in a high-resolution image database, as in real-world situations, high-resolution or high-quality photographs may be difficult or impossible to acquire. Video surveillance is one of the most important prospective application fields for LRFR systems. The video sequences captured by surveillance cameras will need to be analyzed automatically as the number of cameras increases, particularly in urban areas. This work presents the challenges of that face recognition system (FRS) and an in-depth review of the dataset used for training and testing the LRFR system and the method used in the LRFR system.