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Item
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Finger Vein Recognition based on Histogram of Oriented Gradients (HOG)
http://hdl.handle.net/20.500.12678/0000004886
http://hdl.handle.net/20.500.12678/0000004886a30ebdea-5f64-4d7b-aa0c-f0de9e210804
af522cdf-7a03-44b9-a72f-c2c24b601431
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Publication type | ||||||
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Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Finger Vein Recognition based on Histogram of Oriented Gradients (HOG) | |||||
Language | en | |||||
Publication date | 2017-02-16 | |||||
Authors | ||||||
Htwe, Khin Sabai | ||||||
Aye, Nyein | ||||||
Description | ||||||
In this paper, a Region of Interest (ROI)extraction method is proposed based on labeling veinimages using morphological processing. Firstly,finger vein images are segmented to remove theunwanted background or the shape of the device.Secondly, the images are oriented to correct to solvethe finger displacement’s problem. Thirdly, ROIlocalization method is used to accurately extract theregion of vein vessels. Finally, Histogram of OrientedGradient (HOG) features are extracted to recognizethat person is the genuine or imposter. Segmentedfinger vein and calculated orientation can supporteach other to produce higher accuracy in localizingROIs. In addition, a simple feature differencingmethod is proposed to reduce the calculation time formatching. | ||||||
Keywords | ||||||
finger vein, orientation correction, HOG features, ROI localization, segmentation, edge operator | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/785 | |||||
Journal articles | ||||||
Fifteenth International Conference on Computer Applications(ICCA 2017) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |