scholarly journals Image Similarity Test Using Eigenface Calculation

2017 ◽  
Author(s):  
Andysah Putera Utama Siahaan
Keyword(s):  
Face Recognition ◽  
Digital Images ◽  
Image Similarity ◽  
Original Image ◽  
Human Eye ◽  
Digital Forensic ◽  
Similarity Test

An image is a medium for conveying information. The information contained therein may be a particular event, experience or moment. Not infrequently many images that have similarities. However, this level of similarity is not easily detected by the human eye. Eigenface is one technique to calculate the resemblance of an object. This technique calculates based on the intensity of the colors that exist in the two images compared. The stages used are normalization, eigenface, training, and testing. Eigenface is used to calculate pixel proximity between images. This calculation yields the feature value used for comparison. The smallest value of the feature value is an image very close to the original image. Application of this method is very helpful for analysts to predict the likeness of digital images. Also, it can be used in the field of steganography, digital forensic, face recognition and so forth.

scholarly journals Facial Privacy Preservation using FGSM and Universal Perturbation attacks

2022 ◽  
Author(s):  
Nishchal J
Keyword(s):  
Face Recognition ◽  
Privacy Preservation ◽  
Personal Data ◽  
High Accuracy ◽  
Black Box ◽  
Face Image ◽  
Original Image ◽  
User Privacy ◽  
Human Eye ◽  
Face Images

<p>Recent research has established the possibility of deducing soft-biometric attributes such as age, gender and race from an individual’s face image with high accuracy. Many techniques have been proposed to ensure user privacy, such as visible distortions to the images, manipulation of the original image with new face attributes, face swapping etc. Though these techniques achieve the goal of user privacy by fooling face recognition models, they don’t help the user when they want to upload original images without visible distortions or manipulation. The objective of this work is to implement techniques to ensure the privacy of user’s sensitive or personal data in face images by creating minimum pixel level distortions using white-box and black-box perturbation algorithms to fool AI models while maintaining the integrity of the image, so as to appear the same to a human eye.</p><div><br></div>

scholarly journals MENDETEKSI ORISINALITAS CITRA DIGITAL DENGAN MENERAPKAN METODE ADLER-32

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Jelita Lahagu
Keyword(s):  
Digital Image ◽  
Digital Images ◽  
Image Data ◽  
Original Image ◽  
Image Content ◽  
Human Eye ◽  
Object Based

The development of digital images is now very rapid, where the processing of image data, documents on digital images make images easily created or manipulated easily, even without leaving a visual imprint for users to manipulate an image. The ease in making and changing an image can damage the credibility of the originality / authenticity of the image in various aspects.Image is a combination of points, lines, shapes and colors to create an imitation of an object. Based on this, the pixel changes the original image so that it does not indicate the original image or the image has been manipulated. Thus the detection of the image can be known the authenticity of an image using the Adler-32 Algorithm.  Small changes of pixels do not make the image content detected by the human eye. This is explained in pixels like the long width in the image. The basis of this research is to detect the originality or authenticity of a digital image. Keywords : Image, Originality, Manipulation, Adler-32

scholarly journals Facial Privacy Preservation using FGSM and Universal Perturbation attacks

2022 ◽  
Author(s):  
Nishchal J
Keyword(s):  
Face Recognition ◽  
Privacy Preservation ◽  
Personal Data ◽  
High Accuracy ◽  
Black Box ◽  
Face Image ◽  
Original Image ◽  
User Privacy ◽  
Human Eye ◽  
Face Images

<p>Recent research has established the possibility of deducing soft-biometric attributes such as age, gender and race from an individual’s face image with high accuracy. Many techniques have been proposed to ensure user privacy, such as visible distortions to the images, manipulation of the original image with new face attributes, face swapping etc. Though these techniques achieve the goal of user privacy by fooling face recognition models, they don’t help the user when they want to upload original images without visible distortions or manipulation. The objective of this work is to implement techniques to ensure the privacy of user’s sensitive or personal data in face images by creating minimum pixel level distortions using white-box and black-box perturbation algorithms to fool AI models while maintaining the integrity of the image, so as to appear the same to a human eye.</p><div><br></div>

A CRYPTO SIGNATURE SCHEME FOR IMAGE AUTHENTICATION OVER WIRELESS CHANNEL

2005 ◽  
Vol 05 (01) ◽  
pp. 135-148 ◽  
Author(s):  
QIBIN SUN ◽  
SHUIMING YE ◽  
CHING-YUNG LIN ◽  
SHIH-FU CHANG
Keyword(s):  
Packet Loss ◽  
Digital Signature ◽  
Digital Images ◽  
Image Authentication ◽  
Wireless Channel ◽  
Experimental Results ◽  
Signature Scheme ◽  
Original Image ◽  
Degraded Images ◽  
Block Shuffling

With the ambient use of digital images and the increasing concern on their integrity and originality, consumers are facing an emergent need of authenticating degraded images despite lossy compression and packet loss. In this paper, we propose a scheme to meet this need by incorporating watermarking solution into traditional cryptographic signature scheme to make the digital signatures robust to these image degradations. Due to the unpredictable degradations, the pre-processing and block shuffling techniques are applied onto the image at the signing end to stabilize the feature extracted at the verification end. The proposed approach is compatible with traditional cryptographic signature scheme except that the original image needs to be watermarked in order to guarantee the robustness of its derived digital signature. We demonstrate the effectiveness of this proposed scheme through practical experimental results.

Automatic forensic face recognition from digital images

2004 ◽  
Vol 44 (1) ◽  
pp. 29-34 ◽  
Author(s):  
C. Peacock ◽  
A. Goode ◽  
A. Brett
Keyword(s):  
Face Recognition ◽  
Digital Images

Performing Security on Digital Images

2019 ◽  
pp. 211-246 ◽  
Author(s):  
Abdallah Soualmi ◽  
Lamri Laouamer ◽  
Adel Alti
Keyword(s):  
Real Time ◽  
Digital Images ◽  
Image Watermarking ◽  
Surveillance Systems ◽  
Original Image ◽  
Robust Techniques ◽  
Monitoring And Surveillance ◽  
Robust Image ◽  
Broadcast Monitoring

In image watermarking, information is embedded in the original image for many reasons, such as ownership proofing, alteration detection, and/or fingerprinting, but it can also be used for real-time services such as e-payment, broadcast monitoring, and surveillance systems. For these, the data embedded must be extractable even if the image is manipulated intentionally or unintentionally. In contrast, robust techniques are the kind of watermarking that could assure the authenticity and protect the copyright. Many robust image watermarking approaches have been proposed in the last few years, and the purpose of this chapter is to provide a survey about recent relevant robust image watermarking methods existing in the literature.

scholarly journals Detection of Free-Form Copy-Move Forgery on Digital Images

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Emre Gürbüz ◽  
Guzin Ulutas ◽  
Mustafa Ulutas
Keyword(s):  
Success Rate ◽  
Digital Images ◽  
Research Topic ◽  
High Rate ◽  
High Success Rate ◽  
Free Form ◽  
Gaussian Filtering ◽  
Human Eye ◽  
Production And Distribution ◽  
Active Research

Nowadays, production and distribution of digital images has become part of our life. Since digital images, which are important carriers of information, are considered as the concrete proofs of facts in many fields and they can be used as evidence in the courts of law, development of techniques to ensure image authenticity is an active research topic. Copy-move forgery is one of the most common manipulation techniques that are implemented on the digital images, and various techniques have been developed for detection of these kinds of forgeries. JPEG format, which presents the ability of making high rate compression without causing remarkable changes in the meaning of the image, is the most commonly used format on digital images. In this study, the topic of detecting free-form copy-move forgeries on digital images is covered. It has been observed that the developed technique is able to detect the professional forgeries in which the copied region is selected in free-form and which are almost impossible to be detected by human eye, with high success rate, and it is able to give successful results even if the image is exposed to postprocesses such as JPEG compression and Gaussian filtering, which make the detection of forgery harder.

scholarly journals On identification of human eye retinas by the covariance analysis of their digital images

2013 ◽  
Vol 52 (7) ◽  
pp. 073106 ◽  
Author(s):  
Jonas Skeivalas ◽  
Eimuntas Parseliunas
Keyword(s):  
Digital Images ◽  
Covariance Analysis ◽  
Human Eye
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