Biometric recognition is the study of physiological and behavioral characteristic of person to overcome the problem of Information security.In today modern world,variety of biometric technology are employed,like fingerprints,face,iris or behavioral characteristics such as gait and signature,for automatic identification of an individuals.Among all biometric traits,finger vein recognition(FVR)technology is considered one of the new,reliable and superior biometric modality,which attract the attention of researcher around the globe with its unique advantages.Compared to other biometric technology,FVR system have many advantages,such as anti-counterfeiting,user-friendly,live detection of finger vein,required a small device to capture finger vein image,easy to carry the FVR system.However,image quality of finger vein influence the performance of FVR system.Finger vein image is acquire using NIR(near infra-red light)in illumination transaction method.Therefore,most of the finger vein images prone to non-uniform illumination,low contrast,noise,low brightness problem.These low quality images have a great influence on the performance of FVR systems.Therefore,how to effectively evaluate the quality of finger vein image and how to enhance the low quality finger vein image is still a key issue for FVR system.In this paper,a detail review about various steps is presented i.e.image acquisition,preprocessing,feature extraction and matchingMoreover,we list of the some novel finding after critical finding comparative analysis of the highlighted techniques i.e.traditional finger vein recognition method,Machine Learning and Deep Learning Finger vein identification methods.During performance analysis of various,we find that Image quality is also one of the factor that effect the performance of Finger vein recognition system.Finally,we present a novel method to enhance the quality of finger vein images and improve the performance of the FVR system.To deal with the image quality problem,a novel finger-vein image quality assessment method and an enhancement method are proposed.The proposed finger vein recognition Scheme is based on two folds:(i)Image Quality Assessment,and(ii)Image Enhancement.First,the quality of the image is assessed by the decision tree with r-smote technique,to classify the finger vein image into two classes,i.e.High Quality(HQ)and Low Quality(LQ)images.Second,a single scale retinex filter(SSR)with chromaticity preserved algorithm and Gaussian filter are proposed to enhance the low and high quality finger vein images.To evaluate and test the strength of proposed system,two parameters-namely accuracy and equal error rate(EER)for classifier and recognition performance respectively are employed on a dataset of 1052 Finger vein images.It was determined from experiment that proposed image assessment and enhancement method outperformed other enhancement and assessment scheme,by achieving low error rate of 0.0379.The achieved results show the strength of the proposed art is better than already developed methods in FVR domain.Results also conclude that proposed art would be perfect pre-processing tool for finger vein feature based algorithms.