Recognition of Dorsal Hand Vein Based Bit Planes and Block Mutual Information
| العنوان: | Recognition of Dorsal Hand Vein Based Bit Planes and Block Mutual Information |
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| المؤلفون: | Yuan Yan Tang, Wang Yiding, Jiang Xiaochen, Cao Heng |
| المصدر: | Sensors (Basel, Switzerland) Sensors Volume 19 Issue 17 Sensors, Vol 19, Iss 17, p 3718 (2019) |
| بيانات النشر: | MDPI, 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Brightness, Computer science, dorsal hand vein recognition, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Scale-invariant feature transform, 02 engineering and technology, lcsh:Chemical technology, Biochemistry, Vein recognition, Article, Analytical Chemistry, Pattern Recognition, Automated, Veins, 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, Image Processing, Computer-Assisted, Humans, lcsh:TP1-1185, Computer vision, 030216 legal & forensic medicine, Electrical and Electronic Engineering, mutual information, Instrumentation, block, business.industry, Mutual information, bit planes, Hand, Atomic and Molecular Physics, and Optics, cross-device, Dorsal hand, 020201 artificial intelligence & image processing, Artificial intelligence, business, Algorithms, Bit plane |
| الوصف: | The dorsal hand vein images captured by cross-device may have great differences in brightness, displacement, rotation angle and size. These deviations must influence greatly the results of dorsal hand vein recognition. To solve these problems, the method of dorsal hand vein recognition was put forward based on bit plane and block mutual information in this paper. Firstly, the input gray image of dorsal hand vein was converted to eight-bit planes to overcome the interference of brightness inside the higher bit planes and the interference of noise inside the lower bit planes. Secondly, the texture of each bit plane of dorsal hand vein was described by a block method and the mutual information between blocks was calculated as texture features by three kinds of modes to solve the problem of rotation and size. Finally, the experiments cross-device were carried out. One device was used to be registered, the other was used to recognize. Compared with the SIFT (Scale-invariant feature transform, SIFT) algorithm, the new algorithm can increase the recognition rate of dorsal hand vein from 86.60% to 93.33%. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 1424-8220 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dbb51a6f7b364119b8c0d6a28e7d2382Test http://europepmc.org/articles/PMC6749406Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....dbb51a6f7b364119b8c0d6a28e7d2382 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 14248220 |
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