Evaluation of wavelet transform preprocessing with deep learning aimed at palm vein recognition application

Meirista Wulandari, Basari, Dadang Gunawan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

There are many medical equipments being used by human as assistance to check some organs inside the body. The medical modalities are developed to obtain the most effective and efficient in terms of quality and cost. Research about infrared spectrum as the medical equipment is a highlight among scientists since it can be captured the blood vessel of humans. Infrared penetrates the human skin and be captured by camera. Vein has a pattern and it can be used as human identification system. However, the images need enhancement because of low contrast. Wavelet transforms such as Haar and Daubechies can enhance the quality of vein images. Hence the identification process can be conducted by using deep learning method. In this paper, we use one of convolutional neural networks (CNN) method called AlexNet structure as the deep learning method due to its high performance. As for the wavelet transforms, the Haar wavelet, Daubechies 2, Daubechies 4, and Daubechies 10 are selected for evaluation on palm vein images in the image preprocessing step. As a result, we found that the accuracy of the wavelet transforms and enhanced palm vein images are more than 92%. The highest accuracy can be achieved by applying Daubechies 10 wavelet transform with an accuracy of 93.92%±0.98334.

Original languageEnglish
Title of host publication4th Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, Health, and Medical Devices
Subtitle of host publicationProceedings of the International Symposium of Biomedical Engineering, ISBE 2019
EditorsKenny Lischer, Tomy Abuzairi, Siti Fauziyah Rahman, Misri Gozan
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735419445
DOIs
Publication statusPublished - 10 Dec 2019
Event4th International Symposium of Biomedical Engineering�s Recent Progress in Biomaterials, Drugs Development, Health, and Medical Devices, ISBE 2019 - Padang, West Sumatera, Indonesia
Duration: 22 Jul 201924 Jul 2019

Publication series

NameAIP Conference Proceedings
Volume2193
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference4th International Symposium of Biomedical Engineering�s Recent Progress in Biomaterials, Drugs Development, Health, and Medical Devices, ISBE 2019
CountryIndonesia
CityPadang, West Sumatera
Period22/07/1924/07/19

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Keywords

  • deep learning
  • palm vein
  • recognition
  • wavelet

Cite this

Wulandari, M., Basari, & Gunawan, D. (2019). Evaluation of wavelet transform preprocessing with deep learning aimed at palm vein recognition application. In K. Lischer, T. Abuzairi, S. F. Rahman, & M. Gozan (Eds.), 4th Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, Health, and Medical Devices: Proceedings of the International Symposium of Biomedical Engineering, ISBE 2019 [050005] (AIP Conference Proceedings; Vol. 2193). American Institute of Physics Inc.. https://doi.org/10.1063/1.5139378