scholarly journals Combination of AM and FM screening as security printed feature

2020 ◽  
Author(s):  
Vladislav Vereshchagin ◽  
◽  
Ekaterina Pukhova ◽  
Margarita Khokhlova ◽  
◽  
...  
Keyword(s):  
Digital Image ◽  
Spectral Composition ◽  
Local Binary Patterns ◽  
Suggested Method ◽  
Digital Printing ◽  
Original Image ◽  
Large Variability ◽  
Random Intervals ◽  
Canny Edge ◽  
Printing Techniques

Protection of goods and packaging from counterfeiting and copying, tracking their movement requires improvement of existing labeling and security methods and the development of new ones. Making changes to the image at the prepress stage is the cheapest and easiest way of protection compared to using special printing techniques, special substrates, and inks or additional tags such as RFID. In the article, we suggest a new method to create security printed features, identify them in prints, and confirm the authenticity of the image. The method uses a combination of regular (AM) and stochastic (FM) screening in one image. There are two ways of separating images for AM and FM screening. First is to choose several random intervals in shadows of image tonal distribution and in accordance with values in these intervals original image is separated into two. The second is to separate by structure, for example, use FM screening on edges or textures. We tried Canny edge detector and local binary patterns. By using random values as the parameters, it is possible to generate unique print runs or even individual prints using digital printing. And large variability in the areas of separation gives reason to consider that the suggested method is reliable. Fourier analysis in the suggested method allows not only to detect the presence of security printed features but also to confirm the authenticity of the image on a print. Authentication is implemented by obtaining a digital image of the print by scanning or photographing and comparing the spectral composition of the original image and the digital image of the print. An expert survey showed that after our method presence of a combination of AM and FM screening in images on prints is barely visible. As a result, this method can be used to protect packaging labels with images from copying.

Blind Digital Image Watermarking Algorithm Based on the Chain Code

2012 ◽  
Vol 546-547 ◽  
pp. 410-415
Author(s):  
Chun Ge Tang ◽  
Tie Sheng Fan ◽  
Lei Liu ◽  
Zhi Hui Li
Keyword(s):  
Image Quality ◽  
Digital Watermarking ◽  
Digital Image ◽  
Image Watermarking ◽  
Boundary Representation ◽  
Experimental Results ◽  
Digital Image Watermarking ◽  
Original Image ◽  
Chain Code ◽  
Decision Method

A new blind digital watermarking algorithm based on the chain code is proposed. The chain code is obtained by the characteristics of the original image -the edge contour. The feather can reflect the overall correlation of the vector image, and chain code expression can significantly reduce the boundary representation of the amount of data required. For the watermarking embedding, the original vector image is divided into sub-block images, and two bits of the watermarking information are embedded into sub-block images repeatedly by quantization. For watermarking extracting, the majority decision method is employed to determine the size of the extracted watermark. Experimental results show that the image quality is not significantly lowered after watermarking. The algorithm can resist the basic conventional attacks and has good robustness on the shear attacks.

scholarly journals Modified Lsb For Hiding Encrypted Kurdish Text Into Digital Image

2019 ◽  
Vol 7 (4) ◽  
pp. 254
Author(s):  
Nada E. Tawfiq
Keyword(s):  
Digital Image ◽  
Text Message ◽  
Cover Image ◽  
Second Phase ◽  
Original Image ◽  
Text File ◽  
Least Significant Bit ◽  
Text Information ◽  
Embedded Technique ◽  
Lsb Substitution

Image files can hide text without their size being affected too much. This process called steganography which allows hiding text in images without any suspicions from intruders. This paper addresses an improved LSB substitution algorithm for hiding Kurdish text information written in text file into digital image as steganography technique. The algorithm consists of two main phases, the first phase holds the encryption of the Kurdish text message and the embedded technique while the second phase hold the message extraction followed by decryption to get the original code of each character. The algorithm contains many procedures to enhance this process. Least Significant Bit method is used to hide the Kurdish text, in order to keep the features and characteristics of the original image. Applying the proposed approach shows that it seems work in a best case by hiding and retrieving text from the digital image which is used as a carrier of this text. Delphi 2010 was used to simulate both encrypt-embedded phase and extract-decrypt phase, and the results were obtained with high and security which proved the efficiency of the algorithm, where the hidden Kurdish text didn’t make any distortion or change over the cover image.

scholarly journals Implementation Gifford Method For Digital Image Security

2020 ◽  
Vol 2 (2) ◽  
pp. 237-244
Author(s):  
Fauduziduhu Laia ◽  
Erwin Panggabean
Keyword(s):  
Digital Image ◽  
Stream Cipher ◽  
Rapid Development ◽  
Encryption Algorithm ◽  
Output Function ◽  
Original Image ◽  
Left Shift ◽  
Cryptographic Algorithm ◽  
Xor Operation ◽  
The Right

Rapid development of digital image technology secret causes images require security aspect. Reviews These digital secret image can be encrypted using cryptographic methods. After being encrypted, the image is randomized, so that if it is Obtained by an unauthorized party, the image has no meaning. The cryptographic algorithm used in this study is Gifford method. The Gifford method is a stream cipher, a symmetry encryption algorithm that transforms the data character by character. Gifford has 8 registers filled with key bits. The processes performed by the Gifford method are the Output Function process, the 1-bit Sticky Shift Right process, the 1-bit Left Shift process, the XOR operation and the shift register operation to the right. The decryption process must use the same key as the encryption process in order to Obtain the original image.

scholarly journals Discussion on Redesign of Image from Digital Printing Process

2017 ◽  
Vol 2 (2) ◽  
pp. 45
Author(s):  
Mingying Luo
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Digital Technology ◽  
Processing Method ◽  
Separation Method ◽  
Digital Printing ◽  
Image Process ◽  
Digital Image Process ◽  
Printing Technology ◽  
Printing Quality

Digital printing is an indispensable link in the modern printing technology. It is the traditional pre-press process on the transition to digital technology in imaging technology, the digital printing technology. Digital printing expounds digital image process in the design means and methods and their influences on the printing quality from the angle of separation method, image processing method, etc..

scholarly journals Digital Image Steganography Using Bit Flipping

2018 ◽  
Vol 18 (1) ◽  
pp. 69-80 ◽  
Author(s):  
Aditya Kumar Sahu ◽  
Gandharba Swain ◽  
E. Suresh Babu
Keyword(s):  
Digital Image ◽  
Quality Index ◽  
Signal To Noise Ratio ◽  
The State ◽  
Image Steganography ◽  
Original Image ◽  
Signal To Noise ◽  
Secret Data ◽  
Hiding Capacity ◽  
State Of Art

Abstract This article proposes bit flipping method to conceal secret data in the original image. Here a block consists of 2 pixels and thereby flipping one or two LSBs of the pixels to hide secret information in it. It exists in two variants. Variant-1 and Variant-2 both use 7th and 8th bit of a pixel to conceal the secret data. Variant-1 hides 3 bits per a pair of pixels and the Variant-2 hides 4 bits per a pair of pixels. Our proposed method notably raises the capacity as well as bits per pixel that can be hidden in the image compared to existing bit flipping method. The image steganographic parameters such as, Peak Signal to Noise Ratio (PSNR), hiding capacity, and the Quality Index (Q.I) of the proposed techniques has been compared with the results of the existing bit flipping technique and some of the state of art article.

A Dual Image Scrambling Method Based on Discrete Cosine Transform

2014 ◽  
Vol 556-562 ◽  
pp. 4722-4725
Author(s):  
Qiu Dong Sun ◽  
Jian Cun Zuo ◽  
Yu Feng Shao ◽  
Lin Gui
Keyword(s):  
Discrete Cosine Transform ◽  
Digital Image ◽  
Original Image ◽  
Image Scrambling ◽  
Visual Evaluation ◽  
Space Domain ◽  
Cosine Transform ◽  
Inverse Discrete Cosine Transform ◽  
Dual Image ◽  
Arnold Transformation

Although the general random scrambling based on pixel can achieve a good chaotic effect, but it can not change the histogram of a digital image. We introduce the random scrambling into the domain of discrete cosine transform (DCT) of image and scramble the coefficients of DCT to improve the performance of scrambling. Firstly, we did 2-D discrete cosine transform to the original image. Secondly, we scanned the coefficients matrix of DCT by Zig-Zag scanning to get a 1-D sequence, and then we scrambled this sequence by 1-D random scrambling algorithm. Thirdly, we did inverse Zig-Zag scanning to the scrambled sequence and reconstructed the scrambled image from the chaotic coefficients matrix by 2-D inverse discrete cosine transform. Finally, to further improve the scrambling degree of the reconstructed result, we scrambled it again in space domain to gain the encryption image. Experiments show that this algorithm is effective at visual evaluation and is more stable in scrambling degree than Arnold transformation.

scholarly journals Penapisan Derau Gaussian, Speckle dan Salt&Pepper Pada Citra Warna

2011 ◽  
Vol 5 (3) ◽  
pp. 29
Author(s):  
Ika Purwanti Ningrum ◽  
Agfianto Eko Putra ◽  
Dian Nursantika
Keyword(s):  
Image Quality ◽  
Digital Image ◽  
Color Image ◽  
Median Filter ◽  
Bilateral Filter ◽  
Filter Method ◽  
Noise Filtering ◽  
Original Image ◽  
Average Filter

Quality of digital image can decrease becouse some noises. Noise can come from lower quality of image recorder, disturb when transmission data process and weather. Noise filtering can make image better becouse will filtering that noise from the image and can improve quality of digital image. This research have aim to improve color image quality with filtering noise. Noise (Gaussian, Speckle, Salt&Pepper) will apply to original image, noise from image will filtering use Bilateral Filter method, Median Filter method and Average Filter method so can improve color image quality. To know how well this research do, we use PSNR (Peak Signal to Noise Ratio) criteria with compared original image and filtering image (image after using noise and filtering noise).This research result with noise filtering Gaussian (variance = 0.5), highest PSNR value found in the Bilateral Filter method is 27.69. Noise filtering Speckle (variance = 0.5), highest PSNR value found in the Average Filter method is 34.12. Noise filtering Salt&Pepper (variance = 0.5), highest PSNR value found in the Median Filter method is 31.27. Keywords— Bilateral Filter, image restoration, derau Gaussian, Speckle dan Salt&Pepper

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