Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging.
Jerzy FiołkaKrzysztof BernackiAlejandro FarahAdam PopowiczPublished in: Sensors (Basel, Switzerland) (2023)
Personal identification using analysis of the internal and external characteristics of the human finger is currently an intensively developed topic. The work in this field concerns new methods of feature extraction and image analysis, mainly using modern artificial intelligence algorithms. However, the quality of the data and the way in which it is obtained determines equally the effectiveness of identification. In this article, we present a novel device for extracting vision data from the internal as well as external structures of the human finger. We use spatially selective backlight consisting of NIR diodes of three wavelengths. The fast image acquisition allows for insight into the pulse waveform. Thanks to the external illuminator, images of the skin folds of the finger are acquired as well. This rich collection of images is expected to significantly enhance identification capabilities using existing and future classic and AI-based computer vision techniques. Sample data from our device, before and after data processing, have been shared in a publicly available database.
Keyphrases
- deep learning
- artificial intelligence
- big data
- machine learning
- electronic health record
- endothelial cells
- randomized controlled trial
- blood pressure
- optical coherence tomography
- induced pluripotent stem cells
- fluorescence imaging
- emergency department
- light emitting
- soft tissue
- current status
- wound healing
- drug induced