Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

IR Frequency Region: Fingerprint Region

IR Frequency Region: Fingerprint Region

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Efficacy and safety analysis of double plasma molecular adsorption system plus plasma exchange for treating acute-on-chronic liver failure.

American journal of translational research·2026

Same author

Plasma exchange-based artificial liver support system demonstrates short-term therapeutic efficacy in treating chronic severe hepatitis B.

American journal of translational research·2026

Same author

RNA-binding proteins: a novel target for modulating glucose and lipid metabolism.

Signal transduction and targeted therapy·2025

Same author

Evaluating and Enhancing Face Anti-Spoofing Algorithms for Light Makeup: A General Detection Approach.

Sensors (Basel, Switzerland)·2025

Same author

A Two-Stream Method for Human Action Recognition Using Facial Action Cues.

Sensors (Basel, Switzerland)·2024

Same author

Self-Supervised 3D Action Representation Learning With Skeleton Cloud Colorization.

IEEE transactions on pattern analysis and machine intelligence·2023

Same journal

Human-like scene graph generation and evaluation.

Multimedia tools and applications·2026

Same journal

LuGSAM: a novel framework for integrating text prompts to Segment Anything Model (SAM) for segmentation tasks of ICU chest x-rays.

Multimedia tools and applications·2025

Same journal

Brain magnetic resonance image (MRI) segmentation using multimodal optimization.

Multimedia tools and applications·2025

Same journal

Enhancing road safety: In-vehicle sensor analysis of cognitive impairment in older drivers.

Multimedia tools and applications·2025

Same journal

Decision support for augmented reality-based assistance systems deployment in industrial settings.

Multimedia tools and applications·2025

Same journal

Real-time violence detection and localization through subgroup analysis.

Multimedia tools and applications·2025

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 4, 2026

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores

Published on: August 19, 2013

Fast source camera identification using matching signs between query and reference fingerprints.

Yongjian Hu¹, Chang-Tsun Li², Zhimao Lai³

¹School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510640 People's Republic of China.

Multimedia Tools and Applications

|September 1, 2015

Summary

This summary is machine-generated.

This study introduces a novel fast search algorithm for source camera identification using unique camera fingerprints. The method enhances accuracy and efficiency in identifying original image sources, even with degraded fingerprint quality.

Keywords:

Camera fingerprint digest Fast search algorithm Robustness Search Priority Array (SPA)Source camera identification

More Related Videos

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Published on: September 2, 2020

HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis

HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis

Published on: November 11, 2022

Related Experiment Videos

Last Updated: Apr 4, 2026

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores

Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores

Published on: August 19, 2013

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Published on: September 2, 2020

HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis

HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis

Published on: November 11, 2022

Area of Science:

Digital Image Forensics
Computer Vision
Information Security

Background:

Source camera identification is crucial for digital forensics and copyright protection.
Existing fast search algorithms for camera fingerprints are limited, especially for real-world applications with varying image quality.

Purpose of the Study:

To develop a novel, fast search algorithm for efficient source camera identification.
To improve the robustness and accuracy of camera fingerprint matching, even with degraded query fingerprints.

Main Methods:

A new search algorithm utilizing global information from query and reference fingerprints.
Implementation of a lookup table based on a separate-chaining hash table to accelerate the search process.
Testing with real-world photographic images to evaluate performance.

Main Results:

The proposed algorithm demonstrates adaptability to query fingerprints of varying quality.
Achieves higher detection rates compared to traditional brute-force and existing pioneering fast search methods.
Shows a lower computational cost than comparative algorithms.

Conclusions:

The novel fast search algorithm offers a significant advancement in source camera identification.
It provides a robust and computationally efficient solution for real-world applications.
The method effectively handles variations in fingerprint quality, improving identification accuracy.