Source camera identification using noise residual

K. R. Akshatha, H. Anitha, A. K. Karunakar, U. Raghavendra, Dinesh Shetty

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

1 Citation (Scopus)

Abstract

Source camera identification process plays a major role in digital image forensics, which identifies the source camera used for capturing the given image. The state-of-The-Art methods for source camera identification are mainly based on identifying the demosaicing artifacts, sensor noise based artifacts or by using image features from spatial/frequency domain. This paper proposes a novel feature based approach for source camera identification, by making use of the noise patterns present in the images, caused due to the individual source cameras. The scene contents present in the images are eliminated using Gaussian based denoising to estimate the noise patterns present in the images. Higher Order Wavelet Statistics (HOWS) are used as discriminative features and are used with support vector machine (SVM) classifiers to identify the originating source camera of the given image. The experiment has been carried out using the images captured from different cell phone cameras and the obtained results have proved the robustness of the proposed method.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1080-1084
Number of pages5
ISBN (Electronic)9781509007745
DOIs
Publication statusPublished - 05-01-2017
Event1st IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Bangalore, India
Duration: 20-05-201621-05-2016

Conference

Conference1st IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016
CountryIndia
CityBangalore
Period20-05-1621-05-16

Fingerprint

Light sources
Cameras
Support vector machines
Classifiers
Statistics
Sensors
Experiments

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Electrical and Electronic Engineering

Cite this

Akshatha, K. R., Anitha, H., Karunakar, A. K., Raghavendra, U., & Shetty, D. (2017). Source camera identification using noise residual. In 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings (pp. 1080-1084). [7807997] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTEICT.2016.7807997
Akshatha, K. R. ; Anitha, H. ; Karunakar, A. K. ; Raghavendra, U. ; Shetty, Dinesh. / Source camera identification using noise residual. 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1080-1084
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Akshatha, KR, Anitha, H, Karunakar, AK, Raghavendra, U & Shetty, D 2017, Source camera identification using noise residual. in 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings., 7807997, Institute of Electrical and Electronics Engineers Inc., pp. 1080-1084, 1st IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016, Bangalore, India, 20-05-16. https://doi.org/10.1109/RTEICT.2016.7807997

Source camera identification using noise residual. / Akshatha, K. R.; Anitha, H.; Karunakar, A. K.; Raghavendra, U.; Shetty, Dinesh.

2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1080-1084 7807997.

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

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Akshatha KR, Anitha H, Karunakar AK, Raghavendra U, Shetty D. Source camera identification using noise residual. In 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1080-1084. 7807997 https://doi.org/10.1109/RTEICT.2016.7807997