{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T15:59:32Z","timestamp":1781193572862,"version":"3.54.1"},"reference-count":36,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,9,27]],"date-time":"2021-09-27T00:00:00Z","timestamp":1632700800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005605","name":"Universiti Malaysia Pahang","doi-asserted-by":"publisher","award":["RDU1703225"],"award-info":[{"award-number":["RDU1703225"]}],"id":[{"id":"10.13039\/501100005605","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Enhancement of captured hand vein images is essential for a number of purposes, such as accurate biometric identification and ease of medical intravenous access. This paper presents an improved hand vein image enhancement technique based on weighted average fusion of contrast limited adaptive histogram equalization (CLAHE) and fuzzy adaptive gamma (FAG). The proposed technique is applied using three stages. Firstly, grey level intensities with CLAHE are locally applied to image pixels for contrast enhancement. Secondly, the grey level intensities are then globally transformed into membership planes and modified with FAG operator for the same purposes. Finally, the resultant images from CLAHE and FAG are fused using improved weighted averaging methods for clearer vein patterns. Then, matched filter with first-order derivative Gaussian (MF-FODG) is employed to segment vein patterns. The proposed technique was tested on self-acquired dorsal hand vein images as well as images from the SUAS databases. The performance of the proposed technique is compared with various other image enhancement techniques based on mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measurement (SSIM). The proposed enhancement technique\u2019s impact on the segmentation process has also been evaluated using sensitivity, accuracy, and dice coefficient. The experimental results show that the proposed enhancement technique can significantly enhance the hand vein patterns and improve the detection of dorsal hand veins.<\/jats:p>","DOI":"10.3390\/s21196445","type":"journal-article","created":{"date-parts":[[2021,9,27]],"date-time":"2021-09-27T22:16:38Z","timestamp":1632780998000},"page":"6445","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Dorsal Hand Vein Image Enhancement Using Fusion of CLAHE and Fuzzy Adaptive Gamma"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3205-3900","authenticated-orcid":false,"given":"Marlina","family":"Yakno","sequence":"first","affiliation":[{"name":"Faculty of Electrical and Electronic Engineering Technology, Universiti Malaysia Pahang, Pekan 26600, Pahang, Malaysia"},{"name":"School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal 14300, Pulau Pinang, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3447-6050","authenticated-orcid":false,"given":"Junita","family":"Mohamad-Saleh","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal 14300, Pulau Pinang, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohd Zamri","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Faculty of Electrical and Electronic Engineering Technology, Universiti Malaysia Pahang, Pekan 26600, Pahang, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.compeleceng.2014.11.008","article-title":"Finger knuckle biometrics\u2014A review","volume":"45","author":"Usha","year":"2015","journal-title":"Comput. Electr. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wang, Y., Cao, H., Jiang, X., and Tang, Y. (2019). Recognition of Dorsal Hand Vein Based Bit Planes and Block Mutual Information. Sensors, 19.","DOI":"10.3390\/s19173718"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Pan, C.-T., Francisco, M.D., Yen, C.-K., Wang, S.-Y., and Shiue, Y.-L. (2019). Vein Pattern Locating Technology for Cannulation: A Review of the Low-Cost Vein Finder Prototypes. Sensors, 19.","DOI":"10.3390\/s19163573"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Nguyen, D.T., Yoon, H.S., Pham, T.D., and Park, K.R. (2017). Spoof Detection for Finger-Vein Recognition System Using NIR Camera. Sensors, 17.","DOI":"10.3390\/s17102261"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Hong, H.G., Lee, M.B., and Park, K.R. (2017). Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors. Sensors, 17.","DOI":"10.3390\/s17061297"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/s11548-018-1865-9","article-title":"Real-time dual-modal vein imaging system","volume":"14","author":"Mela","year":"2018","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"159821","DOI":"10.1109\/ACCESS.2019.2950698","article-title":"Adaptive Learning Gabor Filter for Finger-Vein Recognition","volume":"7","author":"Zhang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_8","first-page":"3221","article-title":"Embedded Vein Recognition System with Wavelet Domain","volume":"32","author":"Hsia","year":"2020","journal-title":"Sens. Mater."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"380","DOI":"10.5455\/aim.2016.24.380-384","article-title":"Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques","volume":"24","author":"Bayani","year":"2016","journal-title":"Acta Inform. Med."},{"key":"ref_10","first-page":"7","article-title":"Image Fusion Techniques: A Review","volume":"130","author":"Mishra","year":"2015","journal-title":"Int. J. Comput. Appl."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1174","DOI":"10.1016\/j.proeng.2012.06.149","article-title":"Enhancement of vein patterns in hand image for biometric and biomedical application using various image enhancement techniques","volume":"38","author":"Deepak","year":"2012","journal-title":"Procedia Eng."},{"key":"ref_12","first-page":"132","article-title":"A Comparison of the Vein Patterns in Hand Images with other image enhancement","volume":"5","author":"Chithra","year":"2016","journal-title":"Int. J. Emerg. Trends Technol. Comput. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1016\/j.compeleceng.2017.09.012","article-title":"Contrast enhancement of brightness-distorted images by improved adaptive gamma correction","volume":"66","author":"Cao","year":"2018","journal-title":"Comput. Electr. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1186\/s13640-016-0138-1","article-title":"An adaptive gamma correction for image enhancement","volume":"2016","author":"Rahman","year":"2016","journal-title":"EURASIP J. Image Video Process."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Yakno, M., Saleh, J.M., and Rosdi, B.A. (2011, January 16\u201318). Low contrast hand vein image enhancement. Proceedings of the 2011 IEEE International Conference on Signal and Image Processing Applications, ICSIPA, Kuala Lumpur, Malaysia.","DOI":"10.1109\/ICSIPA.2011.6144135"},{"key":"ref_16","first-page":"309","article-title":"Non-Invasive Vein Detection using Infra-red Rays","volume":"5","author":"Singh","year":"2016","journal-title":"Int. J. Adavanced Res. Comput. Commun. Eng."},{"key":"ref_17","first-page":"12","article-title":"Vein Detection Using Infrared for Venepuncture","volume":"4","author":"Ranade","year":"2017","journal-title":"Int. J. Trend Res. Dev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.11591\/eei.v8i3.1514","article-title":"Smartphone Aided Real-Time Blood Vein Detection System","volume":"8","author":"Ahmed","year":"2019","journal-title":"Bull. Electr. Eng. Inform."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"60850","DOI":"10.1109\/ACCESS.2019.2914721","article-title":"A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer","volume":"7","author":"Yildiz","year":"2019","journal-title":"IEEE Access"},{"key":"ref_20","first-page":"2913","article-title":"A novel technique for forearm blood vein detection and enhancement","volume":"28","author":"Francis","year":"2017","journal-title":"Biomed. Res."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Li, S., Zhang, H., Shi, Y., and Yang, J. (2019). Novel Local Coding Algorithm for Finger Multimodal Feature Description and Recognition. Sensors, 19.","DOI":"10.3390\/s19092213"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Li, X., Li, Z., Yang, D., Zhong, L., Huang, L., and Lin, J. (2020). Research on Finger Vein Image Segmentation and Blood Sampling Point Location in Automatic Blood Collection. Sensors, 21.","DOI":"10.3390\/s21010132"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1179\/1743131X14Y.0000000070","article-title":"Gaussian directional pattern for dorsal hand vein recognition","volume":"63","author":"Hsu","year":"2013","journal-title":"Imaging Sci. J."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"17089","DOI":"10.3390\/s150717089","article-title":"Intensity Variation Normalization for Finger Vein Recognition Using Guided Filter Based Singe Scale Retinex","volume":"15","author":"Xie","year":"2015","journal-title":"Sensors"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2565","DOI":"10.1364\/BOE.7.002565","article-title":"Augmented reality based real-time subcutaneous vein imaging system","volume":"7","author":"Ai","year":"2016","journal-title":"Biomed. Opt. Express"},{"key":"ref_26","first-page":"43","article-title":"Palm vein recognition based on 2D-discrete wavelet transform and linear discrimination analysis","volume":"6","author":"Elnasir","year":"2014","journal-title":"Int. J. Adv. Soft Comput. Appl."},{"key":"ref_27","first-page":"312","article-title":"A New Preprocessing Algorithm of Hand Vein Image","volume":"462\u2013463","author":"Liu","year":"2013","journal-title":"Appl. Mech. Mater."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1209","DOI":"10.13005\/bpj\/1482","article-title":"Medical Image Fusion: A Brief Introduction","volume":"11","author":"Dogra","year":"2018","journal-title":"Biomed. Pharmacol. J."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"6369","DOI":"10.1007\/s11042-020-08834-5","article-title":"Survey study of multimodality medical image fusion methods","volume":"80","author":"Tawfik","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.infrared.2019.02.010","article-title":"Development of a low-cost microcomputer based vein imaging system","volume":"98","author":"Yildiz","year":"2019","journal-title":"Infrared Phys. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1179\/1743131X12Y.0000000049","article-title":"Dorsal hand vein recognition based on 2D Gabor filters","volume":"62","author":"Lee","year":"2013","journal-title":"Imaging Sci. J."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1007\/s11277-019-06184-6","article-title":"Triangular Fuzzy Membership-Contrast Limited Adaptive Histogram Equalization (TFM-CLAHE) for Enhancement of Multimodal Biometric Images","volume":"106","author":"Vidya","year":"2019","journal-title":"Wirel. Pers. Commun."},{"key":"ref_33","first-page":"1","article-title":"Efficient Medical Image Enhancement using CLAHE Enhancement and Wavelet Fusion","volume":"167","author":"Bhan","year":"2017","journal-title":"Int. J. Comput. Appl."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"044003","DOI":"10.1117\/1.JMI.3.4.044003","article-title":"Blood vessel extraction of diabetic retinopathy using optimized enhanced images and matched filter","volume":"3","author":"Subudhi","year":"2016","journal-title":"J. Med. Imaging"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"99830","DOI":"10.1109\/ACCESS.2019.2930329","article-title":"Enhancement of Retinal Image From Line-Scanning Ophthalmoscope Using Generative Adversarial Networks","volume":"7","author":"Li","year":"2019","journal-title":"IEEE Access"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Tang, M., Teoh, S., Ibrahim, H., and Embong, Z. (2021). Neovascularization Detection and Localization in Fundus Images Using Deep Learning. Sensors, 21.","DOI":"10.3390\/s21165327"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/19\/6445\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:05:45Z","timestamp":1760166345000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/19\/6445"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,27]]},"references-count":36,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2021,10]]}},"alternative-id":["s21196445"],"URL":"https:\/\/doi.org\/10.3390\/s21196445","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,27]]}}}