Automatic Source Camera Identification Technique Based-on Hierarchy Clustering Method

2021 ◽  
pp. 715-723
Author(s):  
Zhimao Lai ◽  
Yufei Wang ◽  
Weize Sun ◽  
Peng Zhang
Keyword(s):  
Clustering Method ◽  
Source Camera Identification ◽  
Camera Identification ◽  
Identification Technique

Wavelet energy feature based source camera identification for ear biometric images

2020 ◽  
Vol 130 ◽  
pp. 139-147 ◽  
Author(s):  
Debbrota Paul Chowdhury ◽  
Sambit Bakshi ◽  
Pankaj Kumar Sa ◽  
Banshidhar Majhi
Keyword(s):  
Wavelet Energy ◽  
Source Camera Identification ◽  
Camera Identification ◽  
Feature Based ◽  
Energy Feature

scholarly journals Source Camera Identification Issues

2011 ◽  
Vol 3 (4) ◽  
pp. 1-15
Author(s):  
Yongjian Hu ◽  
Chang-Tsun Li ◽  
Changhui Zhou ◽  
Xufeng Lin
Keyword(s):  
Classification Accuracy ◽  
Selection Criteria ◽  
Current Source ◽  
Image Features ◽  
Forensic Identification ◽  
Forensic Investigation ◽  
Identification Schemes ◽  
Source Camera Identification ◽  
Camera Identification ◽  
Popular Image

Statistical image features play an important role in forensic identification. Current source camera identification schemes select image features mainly based on classification accuracy and computational efficiency. For forensic investigation purposes; however, these selection criteria are not enough. Consider most real-world photos may have undergone common image processing due to various reasons, source camera classifiers must have the capability to deal with those processed photos. In this work, the authors first build a sample camera classifier using a combination of popular image features, and then reveal its deficiency. Based on the experiments, suggestions for the design of robust camera classifiers are given.

Source Camera Identification Based on Sensor Readout Noise

2010 ◽  
Vol 2 (3) ◽  
pp. 28-42 ◽  
Author(s):  
H. R. Chennamma ◽  
Lalitha Rangarajan
Keyword(s):  
Computer Software ◽  
Sensor Data ◽  
Processing Parameter ◽  
Source Camera Identification ◽  
Camera Identification ◽  
Novel Approach ◽  
Deviation Plot ◽  
Readout Noise ◽  
The One ◽  
Imaging Sensor

A digitally developed image is a viewable image (TIFF/JPG) produced by a camera’s sensor data (raw image) using computer software tools. Such images might use different colour space, demosaicing algorithms or by different post processing parameter settings which are not the one coded in the source camera. In this regard, the most reliable method of source camera identification is linking the given image with the sensor of camera. In this paper, the authors propose a novel approach for camera identification based on sensor’s readout noise. Readout noise is an important intrinsic characteristic of a digital imaging sensor (CCD or CMOS) and it cannot be removed. This paper quantitatively measures readout noise of the sensor from an image using the mean-standard deviation plot, while in order to evaluate the performance of the proposed approach, the authors tested against the images captured at two different exposure levels. Results show datasets containing 1200 images acquired from six different cameras of three different brands. The success of proposed method is corroborated through experiments.

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