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Related Concept Videos

IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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Design Example: Resistive Touchscreen01:14

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A device engineer plays a crucial role in designing user interfaces for mobile devices. One such interface is the resistive touchscreen, which fundamentally consists of two metallic layers: a flexible upper layer and a rigid lower layer, separated by a narrow gap. The high resistance between these two layers is a key characteristic of this design.
When a user touches the screen, the two layers make contact at a specific point known as the touchpoint. This contact reduces the resistance between...
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Related Experiment Video

Updated: Mar 26, 2026

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut
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FingerScanner: Embedding a Fingerprint Scanner in a Raspberry Pi.

Jordi Sapes1, Francesc Solsona2

  • 1Department of Computer Science and INSPIRES, University of Lleida, Jaume II 69, Lleida 25001, Spain. jordisapes@gmail.com.

Sensors (Basel, Switzerland)
|February 11, 2016
PubMed
Summary

This study presents a low-cost fingerprint recognition system. It is embedded into a Raspberry Pi with Linux, making commercial products more competitive.

Keywords:
Raspberry Piembeddingfingerprintwebsite

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Biometrics

Background:

  • Growing interest in embedded systems.
  • Increased use of Linux and Raspberry Pi platforms due to cost reduction.
  • Need for competitive commercial products through embedded devices.

Purpose of the Study:

  • To present a low-cost fingerprint recognition system.
  • To embed this system into a Raspberry Pi with Linux.

Main Methods:

  • Utilizing Raspberry Pi hardware.
  • Implementing a Linux-based operating system.
  • Developing a fingerprint recognition algorithm.

Main Results:

  • A functional low-cost fingerprint recognition system.
  • Successful integration into a Raspberry Pi embedded device.
  • Demonstration of system's potential for commercial applications.

Conclusions:

  • Embedded systems on Raspberry Pi with Linux are viable for commercial products.
  • The developed system offers a cost-effective solution for fingerprint recognition.
  • This approach facilitates the creation of competitive embedded devices.