This study proposes a new system that integrates pulse wave detection and personal authentication using compound eye optics. This system uses an individual's vein pattern for authentication and clearly identifies the individual based on the vein's running pattern. To measure pulse waves, the technique applies a wavelength filter to each segment of a compound eye image and analyzes the collected wavelength information. This approach provides a non-intrusive yet reliable method of personal identification that surpasses traditional methods such as fingerprinting. Vein patterns have the advantage of remaining constant throughout an individual's lifetime, unlike fingerprints, which can change due to a variety of factors. Our system is based on a TOMBO (Thin Observation of Bound Optics) camera, which consists of a lens array, a bulkhead to prevent light leakage, and a CMOS image sensor. We describe in detail the construction and validation of a vein authentication system that works effectively with filters at wavelengths of 940 nm, 850 nm, and 740 nm. By integrating these components, we propose a robust and efficient system for both pulse wave measurement and personal authentication.
We propose a method of detecting respiration curve for the Drowsiness Predicting system based on optical image information processing. It is well known that a falling sleep relate to respiration. This paper focus on a frequency and amplitude of respiration while driving to predict a moment of a falling sleep. Proposed system composed of video camera and image processing unit. Video camera capture time-series image while driving. Image processing unit calculate subtract images per any frame. The respiration ratio is extracted to analysis the time-series signal. In this paper, we have developed a test bed system, and evaluate our system in comparison with a medical device.
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