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 language | English |
|---|---|
| Title of host publication | 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1080-1084 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781509007745 |
| DOIs | |
| Publication status | Published - 05-01-2017 |
| Event | 1st IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Bangalore, India Duration: 20-05-2016 → 21-05-2016 |
Conference
| Conference | 1st IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 |
|---|---|
| Country | India |
| City | Bangalore |
| Period | 20-05-16 → 21-05-16 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Computer Science Applications
- Information Systems
- Electrical and Electronic Engineering
Cite this
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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 proceeding › Conference contribution
TY - GEN
T1 - Source camera identification using noise residual
AU - Akshatha, K. R.
AU - Anitha, H.
AU - Karunakar, A. K.
AU - Raghavendra, U.
AU - Shetty, Dinesh
PY - 2017/1/5
Y1 - 2017/1/5
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85015093268&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85015093268&partnerID=8YFLogxK
U2 - 10.1109/RTEICT.2016.7807997
DO - 10.1109/RTEICT.2016.7807997
M3 - Conference contribution
SP - 1080
EP - 1084
BT - 2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -