基于自适应融合的手掌静脉增强方法
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摘要
针对掌脉轮廓不清晰,图像对比度低、亮度低,进而导致识别性能降低的现象,提出一种自适应融合的手掌静脉增强方法。首先,基于暗原色先验(DCP)去雾算法,根据掌脉图像变异系数自适应选择去雾系数,得到DCP增强图像,并且基于部分子块重叠直方图均衡(POSHE)算法得到POSHE增强图像;然后,将图像分为16个子块,依据图像灰度均值与标准差确定各子块权重;最后,根据各子块权重对DCP和POSHE增强图像进行自适应融合,得到最终增强图像。该方法既保留了DCP算法在增强图像对比度和亮度的同时不引入明显噪声的优点,又保留了POSHE算法在增强图像对比度和亮度的同时不损失局部细节的特点;同时,两者的自适应融合既解决了DCP图像阴影部分掌脉缺失现象,又削弱了POSHE产生的块效应。在对两个公开库和自建库分别进行的实验中,三个数据库的等错误率分别为0.000 4、0.047 2、0.057 9,识别率分别为99.98%、94.27%、92.05%。实验结果表明,与现有的图像增强方法相比,该方法降低了等错误率,提高了识别精度。
To solve the degradation of recognition performance caused by unclear palm vein contour, low image contrast and brightness, a new palm vein enhancement method based on adaptive fusion was proposed. Firstly, based on Dark Channel Prior(DCP) defogging algorithm and adaptively selected defogging coefficient according to variation coefficient of the palm vein image, DCP enhanced image was obtained. And based on Partial Overlapped Sub-block Histogram Equalization(POSHE) algorithm, POSHE enhanced image was obtained. Secondly, the image was divided into 16 sub-blocks, and the weight of each sub-block was determined by the gray mean and the standard deviation. Finally, two kinds of enhanced images were fused adaptively according to the weight of each sub-block, obtaining the adaptive fused enhanced image. This method not only retains the advantages of DCP algorithm in enhancing image contrast and brightness without introducing significant noise, but also preserves the benefits of POSHE algorithm in enhancing image contrast and brightness without losing local details. Meanwhile, adaptive fusion of the two algorithms solves the problem of missing palm vein in shadow areas of DCP images and reduces the blocking artifacts produced by POSHE. Experimental results carried out on two public databases and a self-built database show that the equal error rates are 0.000 4, 0.047 2, 0.057 9 and the correct recognition rates are 99.98%, 94.27%, 92.05% respectively, indicating that compared with existing image enhancement methods, the proposed method reduces the equal error rate and improves the recognition accuracy.
To solve the degradation of recognition performance caused by unclear palm vein contour, low image contrast and brightness, a new palm vein enhancement method based on adaptive fusion was proposed. Firstly, based on Dark Channel Prior(DCP) defogging algorithm and adaptively selected defogging coefficient according to variation coefficient of the palm vein image, DCP enhanced image was obtained. And based on Partial Overlapped Sub-block Histogram Equalization(POSHE) algorithm, POSHE enhanced image was obtained. Secondly, the image was divided into 16 sub-blocks, and the weight of each sub-block was determined by the gray mean and the standard deviation. Finally, two kinds of enhanced images were fused adaptively according to the weight of each sub-block, obtaining the adaptive fused enhanced image. This method not only retains the advantages of DCP algorithm in enhancing image contrast and brightness without introducing significant noise, but also preserves the benefits of POSHE algorithm in enhancing image contrast and brightness without losing local details. Meanwhile, adaptive fusion of the two algorithms solves the problem of missing palm vein in shadow areas of DCP images and reduces the blocking artifacts produced by POSHE. Experimental results carried out on two public databases and a self-built database show that the equal error rates are 0.000 4, 0.047 2, 0.057 9 and the correct recognition rates are 99.98%, 94.27%, 92.05% respectively, indicating that compared with existing image enhancement methods, the proposed method reduces the equal error rate and improves the recognition accuracy.
引文
[1]孟宪静,袭肖明,杨璐,等.基于灰度不均匀矫正和SIFT的手指静脉识别方法[J].南京大学学报(自然科学版),2018,54(1):1-10.(MENG X J,XI X M,YANG L,et al.Finger vein recognition based on intensity inhomogeneity correction and scale invariant tfeature transform[J].Journal of Nanjing University(Natural Science),2018,54(1):1-10.)
[2]KUBANEK M,SMORAWA D,HOLOTYAK T.Feature extraction of palm vein patterns based on two-dimensional density function[C]//ICAISC 2015:Proceedings of the 2015 Artificial Intelligence and Soft Computing,LNCS 9120.Berlin:Springer,2015:101-111.
[3]SHIN K Y,PARK Y H,NGUYEN D T,et al.Finger-vein image enhancement using a fuzzy-based fusion method with Gabor and Retinex filtering[J].Sensors,2014,14(2):3095-3129.
[4]ZHANG L G.A novel algorithm for hand vein enhancement and segmentation based on the Retinex method[EB/OL].[2018-05-10].http://dx.doi.org/10.2495/CECNet130411.
[5]YANG X,JIAN L,WU W,et al.Implementing real-time RCF-Retinex image enhancement method using CUDA[J].Journal of RealTime Image Processing,2018,25(4):1-11.
[6]杨数强,杨杰慧,宋亚龙.手指静脉图像小波增强算法[J].现代电子技术,2013,36(15):73-75.(YANG S Q,YANG J H,SONG Y L.Finger vein image enhancement algorithm based on wavelet transform[J].Modern Electronics Technique,2013,36(15):73-75.)
[7]ZHANG C,FU Y.Research on the image enhancement algorithm based on improved wavelet transform[J].Journal of Convergence Information Technology,2013,8(6):384-392.
[8]陈朋,姜立,王海霞,等.基于散射卷积网络的手指静脉识别方法研究[J].浙江工业大学学报,2018,46(1):56-60.(CHEN P,JIANG L,WANG H X,et al.Finger vein recognition based on scattering convolution network[J].Journal of Zhejiang University of Technology,2018,46(1):56-60.)
[9]HAJIAN A,AMLI D.Sharpness enhancement of finger-vein image based on modified un-sharp mask with Log-Gabor filter[J].Procedia Computer Science,2018,126(7):431-440.
[10]蔡超峰,任景英.基于直方图均衡化的手背静脉图像对比度增强[J].计算机应用,2013,33(4):1125-1127.(CAI C F,REN J.Contrast enhancement of hand vein images based on histogram equalization[J].Journal of Computer Applications,2013,33(4):1125-1127.)
[11]FRANCIS M.An efficient algorithm to enhance near infrared images of blood vein in antecubital fossa based on adaptive histogram equalization[C]//Proceedings on ELSEVIER International Conference on Emerging Trends in Electrical Engineering.Amsterdam:Elsevier,2014:35.
[12]JENA G,JENA S,BONAM V R.Image enhancement using fuzzy set[C]//AHFE 2017:Proceedings of the 2017 Advances in Human Factors in Simulation and Modeling.Berlin:Springer,2017:141-150.
[13]江晓龙,王华彬,王东旭,等.改进的单幅近红外掌纹掌静脉图像融合识别[J/OL].计算机应用研究,2019.[2018-04-12].http://www.arocmag.com/article/02-2019-07-055.html.(JIANG X L,WANG H B,WANG D X,et al.Improved fusion recognition for near infrared palmprint and palm vein image[J/OL].Application Research of Computers,2019.[2018-04-12].http://www.arocmag.com/article/02-2019-07-055.html.)
[14]ZHAO J,TIAN H,X U W,et al.A new approach to hand vein image enhancement[C]//Proceedings of the 2009 Second International Conference on Intelligent Computation Technology and Automation.Piscataway,NJ:IEEE,2009:499-501.
[15]HE K,SUN J,TANG X.Single image haze removal using dark channel prior[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(12):2341-2353.
[16]KIM J Y,KIM L S,HWANG S H.An advanced contrast enhancement using partially overlapped sub-block histogram equalization[J].IEEE Transactions on Circuits&Systems for Video Technology,2001,11(4):475-484.
[17]ZHOU Y,KUMAR A.Human identification using palm-vein images[J].IEEE Transactions on Information Forensics&Security,2011,6(4):1259-1274.
[18]周宇佳,刘娅琴,杨丰,等.基于方向特征的手掌静脉识别[J].中国图象图形学报,2014,19(2):243-252.(ZHOU YJ,LIU Y Q,YANG F,et al.Palm-vein recognition based on oriented features[J].Journal of Image and Graphics,2014,19(2):243-252.)
[19]LIU Y,ZHOU Y,QIU S,et al.Real-time locating method for palmvein image acquisition[C]//ICIG 2015:Proceedings of the2015 Image and Graphics.Berlin:Springer,2015:94-110.
[20]EZHILMARAN D,JOSEPH R B.Finger vein biometric system with type-2 fuzzy enhancement and minutiae matching[C]//Proceedings of the 2017 IEEE Region 10 Symposium.Piscataway,NJ:IEEE,2017:1-4.
[21]KANG W,LIU Y,WU Q,et al.Contact-free palm-vein recognition based on local invariant features[J].PLo S One,2014,9(5):1-12.
[22]QIU S,LIU Y,ZHOU Y,et al.Finger-vein recognition based on dual-sliding window localization and pseudo-elliptical transformer[J].Expert Systems with Applications,2016,64:618-632.
[23]袁玲,黄靖,刘娅琴,等.基于图像融合的去掌纹手掌静脉图像增强方法[J].科学技术与工程,2016,16(36):48-54.(YUAN L,HUANG J,LIU Y Q,et al.Palm vein enhancement algorithm by removing palmprint based on image fusion[J].Science Technology and Engineering,2016,16(36):48-54.)
[2]KUBANEK M,SMORAWA D,HOLOTYAK T.Feature extraction of palm vein patterns based on two-dimensional density function[C]//ICAISC 2015:Proceedings of the 2015 Artificial Intelligence and Soft Computing,LNCS 9120.Berlin:Springer,2015:101-111.
[3]SHIN K Y,PARK Y H,NGUYEN D T,et al.Finger-vein image enhancement using a fuzzy-based fusion method with Gabor and Retinex filtering[J].Sensors,2014,14(2):3095-3129.
[4]ZHANG L G.A novel algorithm for hand vein enhancement and segmentation based on the Retinex method[EB/OL].[2018-05-10].http://dx.doi.org/10.2495/CECNet130411.
[5]YANG X,JIAN L,WU W,et al.Implementing real-time RCF-Retinex image enhancement method using CUDA[J].Journal of RealTime Image Processing,2018,25(4):1-11.
[6]杨数强,杨杰慧,宋亚龙.手指静脉图像小波增强算法[J].现代电子技术,2013,36(15):73-75.(YANG S Q,YANG J H,SONG Y L.Finger vein image enhancement algorithm based on wavelet transform[J].Modern Electronics Technique,2013,36(15):73-75.)
[7]ZHANG C,FU Y.Research on the image enhancement algorithm based on improved wavelet transform[J].Journal of Convergence Information Technology,2013,8(6):384-392.
[8]陈朋,姜立,王海霞,等.基于散射卷积网络的手指静脉识别方法研究[J].浙江工业大学学报,2018,46(1):56-60.(CHEN P,JIANG L,WANG H X,et al.Finger vein recognition based on scattering convolution network[J].Journal of Zhejiang University of Technology,2018,46(1):56-60.)
[9]HAJIAN A,AMLI D.Sharpness enhancement of finger-vein image based on modified un-sharp mask with Log-Gabor filter[J].Procedia Computer Science,2018,126(7):431-440.
[10]蔡超峰,任景英.基于直方图均衡化的手背静脉图像对比度增强[J].计算机应用,2013,33(4):1125-1127.(CAI C F,REN J.Contrast enhancement of hand vein images based on histogram equalization[J].Journal of Computer Applications,2013,33(4):1125-1127.)
[11]FRANCIS M.An efficient algorithm to enhance near infrared images of blood vein in antecubital fossa based on adaptive histogram equalization[C]//Proceedings on ELSEVIER International Conference on Emerging Trends in Electrical Engineering.Amsterdam:Elsevier,2014:35.
[12]JENA G,JENA S,BONAM V R.Image enhancement using fuzzy set[C]//AHFE 2017:Proceedings of the 2017 Advances in Human Factors in Simulation and Modeling.Berlin:Springer,2017:141-150.
[13]江晓龙,王华彬,王东旭,等.改进的单幅近红外掌纹掌静脉图像融合识别[J/OL].计算机应用研究,2019.[2018-04-12].http://www.arocmag.com/article/02-2019-07-055.html.(JIANG X L,WANG H B,WANG D X,et al.Improved fusion recognition for near infrared palmprint and palm vein image[J/OL].Application Research of Computers,2019.[2018-04-12].http://www.arocmag.com/article/02-2019-07-055.html.)
[14]ZHAO J,TIAN H,X U W,et al.A new approach to hand vein image enhancement[C]//Proceedings of the 2009 Second International Conference on Intelligent Computation Technology and Automation.Piscataway,NJ:IEEE,2009:499-501.
[15]HE K,SUN J,TANG X.Single image haze removal using dark channel prior[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(12):2341-2353.
[16]KIM J Y,KIM L S,HWANG S H.An advanced contrast enhancement using partially overlapped sub-block histogram equalization[J].IEEE Transactions on Circuits&Systems for Video Technology,2001,11(4):475-484.
[17]ZHOU Y,KUMAR A.Human identification using palm-vein images[J].IEEE Transactions on Information Forensics&Security,2011,6(4):1259-1274.
[18]周宇佳,刘娅琴,杨丰,等.基于方向特征的手掌静脉识别[J].中国图象图形学报,2014,19(2):243-252.(ZHOU YJ,LIU Y Q,YANG F,et al.Palm-vein recognition based on oriented features[J].Journal of Image and Graphics,2014,19(2):243-252.)
[19]LIU Y,ZHOU Y,QIU S,et al.Real-time locating method for palmvein image acquisition[C]//ICIG 2015:Proceedings of the2015 Image and Graphics.Berlin:Springer,2015:94-110.
[20]EZHILMARAN D,JOSEPH R B.Finger vein biometric system with type-2 fuzzy enhancement and minutiae matching[C]//Proceedings of the 2017 IEEE Region 10 Symposium.Piscataway,NJ:IEEE,2017:1-4.
[21]KANG W,LIU Y,WU Q,et al.Contact-free palm-vein recognition based on local invariant features[J].PLo S One,2014,9(5):1-12.
[22]QIU S,LIU Y,ZHOU Y,et al.Finger-vein recognition based on dual-sliding window localization and pseudo-elliptical transformer[J].Expert Systems with Applications,2016,64:618-632.
[23]袁玲,黄靖,刘娅琴,等.基于图像融合的去掌纹手掌静脉图像增强方法[J].科学技术与工程,2016,16(36):48-54.(YUAN L,HUANG J,LIU Y Q,et al.Palm vein enhancement algorithm by removing palmprint based on image fusion[J].Science Technology and Engineering,2016,16(36):48-54.)