A DFT-Based Analysis to Discern Between Camera and Scanned Images

2012 ◽  
pp. 1-8
Author(s):  
Roberto Caldelli ◽  
Irene Amerini ◽  
Francesco Picchioni
Keyword(s):  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Digital Images ◽  
Experimental Results ◽  
Digital Photo ◽  
Geometrical Features ◽  
Pattern Noise ◽  
Photo Camera ◽  
Sensor Pattern Noise ◽  
Scanned Images

Digital images are generated by different sensors, understanding which kind of sensor has acquired a certain image could be crucial in many application scenarios where digital forensic techniques operate. In this paper a new methodology which permits to establish if a digital photo has been taken by a photo-camera or has been scanned by a scanner is presented. The specific geometrical features of the sensor pattern noise introduced by the sensor are investigated by resorting to a DFT (Discrete Fourier Transform) analysis and consequently the origin of the digital content is assessed. Experimental results are provided to witness the reliability of the proposed technique.

A DFT-Based Analysis to Discern Between Camera and Scanned Images

2010 ◽  
Vol 2 (1) ◽  
pp. 21-29 ◽  
Author(s):  
Roberto Caldelli ◽  
Irene Amerini ◽  
Francesco Picchioni
Keyword(s):  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Digital Content ◽  
Digital Photo ◽  
Digital Forensic ◽  
Geometrical Features ◽  
Pattern Noise ◽  
Photo Camera ◽  
Sensor Pattern Noise ◽  
Scanned Images

Digital images are generated by different sensors, understanding which kind of sensor has acquired a certain image could be crucial in many application scenarios where digital forensic techniques operate. In this article a new methodology which permits to establish if a digital photo has been taken by a photo-camera or has been scanned by a scanner is presented. The specific geometrical features of the sensor pattern noise introduced by the sensor are investigated by resorting to a DFT (Discrete Fourier Transform) analysis and consequently the origin of the digital content is assessed. Experimental results are provided to witness the reliability of the proposed technique.

scholarly journals Application of two-dimensional fast Fourier transform algorithm, analog of the Cooley-Tukey algorithm, for 4k fixed format digital image of satellite data in frequency domain processing

2020 ◽  
Vol 149 ◽  
pp. 02010 ◽  
Author(s):  
Mikhail Noskov ◽  
Valeriy Tutatchikov
Keyword(s):  
Fourier Transform ◽  
Numerical Experiment ◽  
Fast Fourier Transform ◽  
Frequency Domain ◽  
Discrete Fourier Transform ◽  
Satellite Data ◽  
Digital Image ◽  
Digital Images ◽  
Two Dimensional ◽  
Fast Fourier Transform Algorithm

Currently, digital images in the format Full HD (1920 * 1080 pixels) and 4K (4096 * 3072) are widespread. This article will consider the option of processing a similar image in the frequency domain. As an example, take a snapshot of the earth's surface. The discrete Fourier transform will be computed using a two-dimensional analogue of the Cooley-Tukey algorithm and in a standard way by rows and columns. Let us compare the required number of operations and the results of a numerical experiment. Consider the examples of image filtering.

DFT TECHNIQUES FOR SIZE ESTIMATION OF DATABASE JOIN OPERATIONS

1999 ◽  
Vol 10 (01) ◽  
pp. 81-102 ◽  
Author(s):  
KAMİl SARAÇ ◽  
ÖMER EĞECİOĞLU ◽  
AMR EL ABBADI
Keyword(s):  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Frequency Distribution ◽  
Fourier Coefficients ◽  
Experimental Results ◽  
Direct Approach ◽  
Size Estimation ◽  
Logarithmic Space ◽  
Novel Algorithms ◽  
Special Case

Novel algorithms based on the Discrete Fourier Transform (DFT) are proposed to estimate the size of relations resulting from join operations. We start with an approach in which the frequency distribution values are transformed using the DFT and the Fourier coefficients are used to construct histograms. Our main contribution is a direct approach which uses the amplitudes of the DFT coefficients iteratively. The proposed algorithm gives the exact join size using logarithmic space for the special case of self join. A generalization to compute the join of arbitrary relations is then used to develop two tree-based techniques that provide a spectrum of algorithms which interpolate storage requirements versus accuracy of the estimation obtained. Finally, we present experimental results to exhibit the effectiveness of our approach.

scholarly journals Image Encryption Using Chaotic Cat Mapping in the Discrete Fourier Transform

2018 ◽  
Vol 18 ◽  
pp. 7389-7397
Author(s):  
Mohammed Alzain
Keyword(s):  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Image Encryption ◽  
Experimental Results ◽  
Transform Domain ◽  
Two Dimensional ◽  
Encrypted Image ◽  
Image Cryptosystem ◽  
Fourier Transform Domain

The paper presents an secure image using the two dimensional chaotic cat mapping  (2D-CCM) in the Discrete Fourier Transform domain (DFT). The ciphering phase begins by applying the DFT on the plainimage to be encrypted and the resulted Fourier transformed image are scrambled using the 2D-CCM and finally an inverse DFT is applied to obtain the final encrypted image. The decryption phase applies a reverse  procedure to get the original plainimage. A set of encryption test experiments are employed to inspect the proposed DFT based 2D-CCM image cryptosystem. The experimental results verified and confirmed the superiority of the proposed DFT based 2D-CCM image cryptosystem.

scholarly journals Screen-Shooting Resilient Watermarking Scheme via Learned Invariant Keypoints and QT

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6554
Author(s):  
Li Li ◽  
Rui Bai ◽  
Shanqing Zhang ◽  
Chin-Chen Chang ◽  
Mengtao Shi
Keyword(s):  
Neural Networks ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Tensor Decomposition ◽  
Experimental Results ◽  
Robust Watermark ◽  
Watermark Embedding ◽  
Extraction Stage ◽  
Watermarking Scheme ◽  
Watermark Algorithm

This paper proposes a screen-shooting resilient watermarking scheme via learned invariant keypoints and QT; that is, if the watermarked image is displayed on the screen and captured by a camera, the watermark can be still extracted from the photo. A screen-shooting resilient watermarking algorithm should meet the following two basic requirements: robust keypoints and a robust watermark algorithm. In our case, we embedded watermarks by combining the feature region filtering model to SuperPoint (FRFS) neural networks, quaternion discrete Fourier transform (QDFT), and tensor decomposition (TD). First we applied FRFS to locate the embedding feature regions which are decided by the keypoints that survive screen-shooting. Second, we structured watermark embedding regions centered at keypoints. Third, the watermarks were embedded by the QDFT and TD (QT) algorithm, which is robust for capturing process attacks. In a partial shooting scenario, the watermark is repeatedly embedded into different regions in an image to enhance robustness. Finally, we extracted the watermarks from at least one region at the extraction stage. The experimental results showed that the proposed scheme is very robust for camera shooting (including partial shooting) different shooting scenarios, and special attacks. Moreover, the efficient mechanism of screen-shooting resilient watermarking could have propietary protection and leak tracing applications.

PERBAIKAN CITRA RGB DENGAN METODE HOMOMORPHIC FILTERING MENGGUNAKAN BUTTERWORTH FILTER

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
TM Irsan Rizky ◽  
Nelly Astuti Hasibuan ◽  
Rian Syahputra
Keyword(s):  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Digital Images ◽  
Filtering Method ◽  
Photo Album ◽  
Black Spots ◽  
Homomorphic Filtering ◽  
Image Improvement ◽  
Rgb Images

The photo is made into a visual recording that has historical value or a memento. However, many memorable photos no longer look good and have noise due to the effectiveness of nature such as the evaporation of liquid that is around the image, it can also be dust or water on the surface of the image, besides that the noise can also be caused by plastic and paper materials that contained in the place where the image is stored as a photo album. For noise caused when taking digital images from camera devices can be in the form of a smoke or light coil that causes the image display is not clear. When the process of capturing RGB images often encountered noise such as black spots. Noise can be improved with several image enhancement techniques such as smoothing, leveling, and convolution. One of the improvements in noise in digital images can be done with Homomorphic filtering Method. Image improvement using the Homomorphic filtering method followed by Butterworth Filtering is part of the discrete fourier transform algorithm which confirms a concept that is rarely used to improve RGB images. However, this can be proven in the form of testing to eliminate noise in improving the quality of RGB images..Keywords: image, homomorphic, butterworth, filtering, RGB, noise

DISTRIBUTED MULTIRESOLUTION DISCRETE FOURIER TRANSFORM AND ITS APPLICATION TO WATERMARKING

2010 ◽  
Vol 08 (02) ◽  
pp. 225-241 ◽  
Author(s):  
GAURAV BHATNAGAR ◽  
BALASUBRAMANIAN RAMAN
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Digital Watermarking ◽  
Singular Values ◽  
Experimental Results ◽  
The Core ◽  
Core Idea ◽  
The Fourier Transform ◽  
Watermarking Scheme

The Fourier transform is undoubtedly one of the most valuable and frequently used tools in signal processing and analysis but it has some limitations. In this paper, we rectify these limitations by proposing a newer version of Fourier transform, namely, Distributed Multiresolution Discrete Fourier Transform (D-MR-DFT) and its application in digital watermarking. The core idea of the proposed watermarking scheme is to decompose an image into four frequency sub-bands using D-MR-DFT and then singular values of every sub-band are modified with the singular values of the watermark. The experimental results show better visual imperceptibility and resiliency of the proposed scheme against intentional or unintentional variety of attacks.

On the Performance of Li’s Unsupervised Image Classifier and the Optimal Cropping Position of Images for Forensic Investigations

2011 ◽  
Vol 3 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Ahmad Ryad Soobhany ◽  
Richard Leary ◽  
KP Lam
Keyword(s):  
Error Rate ◽  
Digital Imaging ◽  
Cross Validation ◽  
Digital Images ◽  
Sample Space ◽  
Forensic Investigation ◽  
Storage Devices ◽  
Pattern Noise ◽  
Sensor Pattern Noise ◽  
Optimal Cropping

Images from digital imaging devices are prevalent in society. The signatures of these images can be extracted as sensor pattern noise (SPN) and classified according to their source devices. In this paper, the authors assess the reliability of an unsupervised classifier for forensic investigation of digital images recovered from storage devices and to identify the best position for cropping the images before processing. Cross validation was performed on the classifier to assess the error rate and determine the effect of the size of the sample space and the classifier trainer on the performance of the classifier. Moreover, the authors find that the effect of saturation and subsequently the contamination of the SPN in the images affected performance negatively. To alleviate the negative performance, the authors identify the areas of images where less contamination occurs to perform cropping.

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