Palm Vein Image Processing and Enhancement in Vein Pattern Recognition System on FPGA

Biometric recognition systems based on hand vein patterns are gaining popularity because they have qualities such as universality, uniqueness, and fraud resistance. Veins are not visible to the human eye since they are positioned beneath the skin, they constitute a strong barrier against deception. The hand's complicated vascular pattern allows for the estimation of a useful number of characteristics for identifying individuals. It has a sanitary advantage over other biometric authentication systems because it is contactless. In a real-world environment, image processing is critical. It's employed in a variety of applications, including security systems, artificial intelligence (AI), and so on. The Field Programmable Gate Array (FPGA) is the best-embedded platform for image processing applications. An FPGA's concurrent architecture allows it to do high-speed picture processing, allowing it to deliver timely warnings. Furthermore, modern FPGAs, particularly small-scale FPGAs, are very effi-cient in terms of cost and power usage. When compared to CPU execution, FPGA video/image computing delivers a processing speedup of ten times. This paper covered filtering approaches, contrast enhancement schemes and segmentation approaches. This paper demonstrates image enhancing techniques and then after results of these techniques are applied on vein images. We implemented an IP based embedded system because it is better in terms of power consumption, area and time. This paper has been work on reducing power as well as hardware utilization to design an optimized system since image processing requires extra hardware and power also.