Dongguk modified DeblurGAN and CNN for recognition of blurred finger-vein image with motion blurred image database
We proposed a motion blurred finger-vein restoration system with modified Blind Motion Deblurring Using Conditional Adversarial Networks (modified DeblurGAN), and a finger-vein recognition system using DenseNet-161. These systems are designed to overcome the performance degradation caused by motion blur. Two open databases named as SDUMLA-HMT-DB [1] and HKPolyU-DB [2] are used for experiment. Finger-vein restoration and recognition models with motion blurred image database are opened to other researchers for fair judgement.
[1] Y. Yin, L. Liu, and X. Sun, "SDUMLA-HMT: A multimodal biometric database", in Proc. 6th Chin. Conf. Biometric Recognit., Beijing, China, Dec. 2011, pp. 260-268.
[2] A. Kumar and Y. Zhou, ‘‘Human identification using finger images,’’ IEEE Trans. Image Process., vol. 21, no. 4, pp. 2228–2244, Apr. 2012.
Any work that uses the provided pretrained network must acknowledge the authors by including the following reference.
Jiho Choi, Jin Seong Hong, Muhammad Owais, Seung Gu Kim, and Kang Ryoung Park, “Restoration of Motion Blurred Image by Modified DeblurGAN for Enhancing the Accuracies of Finger-vein Recognition,” Sensors, in submission
Motion blurred image database is available through this link