An RGB colour image steganography scheme using overlapping block-based pixel-value differencing

Steganography deals with the ways of hiding communicated data in such a way that it remains confidential. Finding best position inside cover image to embed text message, maintaining a reasonable trade-off between security, robustness, higher bit embedding rate and imperceptibility are some of the challenges of steganography system. Hence, this paper presents firefly algorithm for finding best positions inside cover image in order to embed text message into cover image using Pixel Value Differencing (PVD) technique. Four different cover image was used. Experimental result showed the cover image with selected location using firefly algorithm as well as the stego image using PVD technique. The stego image was evaluated using Peak Signal to Noise Ratio (PSNR) and Mean square Error (MSE). Firefly Algorithm with PVD technique produced a promising result for image steganography.

A reversible data hiding scheme provides security for a secret message by embedding it in a cover image. After extracting the secret message at the receiver, the scheme restores the original message and the cover image without any distortion. However, data transmitted by the reversible data hiding scheme is vulnerable to the noise existing on the communications channel. A reversible data hiding scheme using turbo code is proposed in this paper to address that problem. The proposed reversible data hiding integrates modified matrix embedding, turbo code, and syndrome embedding to provide improved embedding capacity, security, and error correction. Modified matrix embedding hides the secret message in the cover image. The resulting stego-image is then encrypted and encoded by the turbo code. Turbo code deploys a secret key interleaver that shuffles the incoming bits using elliptic curve arithmetic and a secret key. The exact recovery of the cover image and the secret message by the receiver depends on the user-specific secret key. Modified matrix embedding hides a large number of secret message bits, which distorts the stegoimage. However, encrypting the stego-image with the secret key interleaver makes the embedding invisible. The proposed syndrome embedding transmits the locations of the modified bits in the cover image, and enables the receiver to reverse the effects of embedding. Simulation results with the proposed scheme demonstrate a high embedding capacity and improved error correction performance of 10-4 for an additive white Gaussian noise (AWGN) channel at an SNR of 2dB. It also successfully recovers the exact cover image and the secret message, compared to existing schemes such as matrix embedding and reversible data hiding in the encrypted domain. Moreover, the results depict high resistance to brute force attacks, statistical attacks, noise attacks, and cropping attacks.

Due to high consumer demand, some traders use the high price of meat to make a profit by mixing pork and buffalo meat. Some consumers are not aware of this, because in plain view buffalo meat with pork meat is difficult to distinguish, especially for some ordinary people. This action is very detrimental and disturbing the local community, especially Muslims. At present, technological advances in the field of digital image processing are increasing rapidly, especially in food products. In general, this research was conducted in 2 (three) stages. The first stage, namely the stage of image data collection of pork and buffalo meat. The second stage, namely the classification of pork and buffalo meat images using image histogram analysis and the Gray Level Co-occurrence Matrix (GLCM) method based on the color and texture of the meat. In this study using the Red Green Blue (RGB) color image method and GLCM texture extraction, namely contrast, homogeneity, energy, and correlation. The study was conducted using 20 samples of meat images (10 images of pork and 10 images of buffalo meat, respectively). Based on the results of the research that has been done, it was found that the image of buffalo meat has a higher percentage value of the Red (R) color component when compared to the pork image, whereas the percentage value of the Green (G) and Blue (B) color components is lower when compared to the image pork. Then, if the value between pixels is not homogeneous (small homogeneity value), then the contrast value is large, and vice versa if the value between pixels is homogeneous (large homogeneity value) then the contrast value is small. The image of buffalo meat has a small homogeneity value compared to the image of pork, so the variation in intensity (contrast) in the image of buffalo meat is high.

Reversible data hiding (RDH) is an active research area in the field of information security. The RDH scheme allows the transmission of a secret message by embedding it into a cover image, and the receiver can recover the original cover image along with the extraction of the secret message. In this paper, we propose a bit plane compression based RDH scheme to hide a sequence of secret message bits into a grayscale image. In the proposed method, a selected bit plane of the cover image will be compressed using run-length encoding (RLE) scheme. Further, the RLE sequence has been efficiently encoded as a binary sequence using Elias gamma encoding method. The Elias gamma encoded bit sequence concatenated with the secret message bits are used to replace the selected bit plane after performing a sequence of Arnold transform. The Arnold transform helps to find a new scrambled version of the bit plane which is very close to the original bit plane to ensure the visual quality of the stego image. The RLE is a lossless compression technique, therefore recovery of the original image is possible by the receiver. The experimental study of the proposed scheme on the images from standard image dataset (USC-SIPI image dataset) shows that the proposed scheme outperforms the existing scheme in terms of the visual quality of the stego image without compromising the data embedding rate.

Blood vessel detection in retinal images is a fundamental step for feature extraction and interpretation of image content. This paper proposes a novel computational paradigm for detection of blood vessels in fundus images based on RGB components and quadtree decomposition. The proposed algorithm employs median filtering, quadtree decomposition, post filtration of detected edges, and morphological reconstruction on retinal images. The application of preprocessing algorithm helps in enhancing the image to make it better fit for the subsequent analysis and it is a vital phase before decomposing the image. Quadtree decomposition provides information on the different types of blocks and intensities of the pixels within the blocks. The post filtration and morphological reconstruction assist in filling the edges of the blood vessels and removing the false alarms and unwanted objects from the background, while restoring the original shape of the connected vessels. The proposed method which makes use of the three color components (RGB) is tested on various images of publicly available database. The results are compared with those obtained by other known methods as well as with the results obtained by using the proposed method with the green color component only. It is shown that the proposed method can yield true positive fraction values as high as 0.77, which are comparable to or somewhat higher than the results obtained by other known methods. It is also shown that the effect of noise can be reduced if the proposed method is implemented using only the green color component.

In spatial domain image steganography, Least Significant Bits (LSB) of cover image pixels are used to embed a secret message due to minimal distortion and higher payload capacity. In this paper, we have introduced an exclusive-OR (XOR) based encoding of encrypted secret message bits using varying higher-order pixel intensity bits. Encoding and LSB embedding is done block-wise by dividing the cover image into a number of blocks. The secret message is first encrypted using symmetric key cryptography and then encoded those encrypted bits by XORing them with randomly selected higher-order pixel bis of the cover image to obscure the secret bits further. Next, an inversion technique is applied to the encoded bits block-wise to keep the LSB bit changes to a minimum. The stego-key consists of the symmetric encryption key and the encode-key containing parameter settings such as the number_of_blocks, starting_block, start_pixel_offset, block_selection_rule, etc. This stego-key is shared prior to the actual communication using public-key cryptography to ensure the key’s authenticity and integrity. The extraction process does not require the cover image; the stego-image and the stego-key are sufficient. Experimental results show the visual imperceptibility along with improved image quality metrics such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Normalized Cross-Correlation (NCC), and Structural Similarity (SSIM) index in comparison to other well-known techniques. The average PSNR value remains above 51dB, even with 90% of the capacity utilized. The proposed scheme successfully eludes many standard steganalysis attacks such as histogram-based analysis (PDH), chi-square based embed probability test, Regular and Singular groups (RS) analysis, sample pair test, etc. on the tested stego-images.

Security in communication is a top priority in the use of steganography. This concept allows us to convey messages to people we want through a media without arousing suspicion to others. In this case the media used is digital media. More specifically digital media used are image media because images are the most popular media in secret message hiding. The increasingly widespread use of the internet as a communication medium is the reason why this message insertion technique uses the PHP programming language that is currently popular as a programming language supporting web-based applications. The LSB (Least Significant Byte) method is a message hiding technique in steganography where the hidden message is hidden by replacing the data bits in the image segment with secret message bits. Secret message bits are inserted in the low bit or the rightmost bit in the pixel composing the image consisting of red, green and blue (RGB), each of which has an 8-bit value of 0 to 255 with binary format 00000000 to 11111111. Thus, 3 bits of data can be inserted in each pixel image available. The LSB method is then applied in a library which is then named as a stegger which has the function to insert messages in images using the PHP programming language. To add protection to messages sent, an encryption algorithm is added that has been arranged in a class named secrypt that is accompanied by keyword inclusion so that the message sent has a higher level of security. Â Keywords : steganography, PHP, encryption, stegger, secrypt

We report quantitative phase imaging of human red blood cells (RBCs) using phase-shifting interference microscopy. Five phase-shifted white light interferograms are recorded using colour charge coupled device camera. White light interferograms were decomposed into red, green, and blue colour components. The phase-shifted interferograms of each colour were then processed by phase-shifting analysis and phase maps for red, green, and blue colours were reconstructed. Wavelength dependent refractive index profiles of RBCs were computed from the single set of white light interferogram. The present technique has great potential for non-invasive determination of refractive index variation and morphological features of cells and tissues.

Steganography is the practice of hiding data, such as images, videos, or text, within a cover image without it being detectable by the human eye. Several factors, such as the capacity, security, and robustness of the technique, are essential when transferring information using this method. In this study, we propose a new approach to image steganography that improves the Least Significant Bit (LSB) technique by utilizing images of 24 bits in each pixel. Improving the capacity and security of LSB-based steganography requires a combination of techniques, such as indirect embedding, embedding in multiple channels, and applying cryptographic and compression techniques. This approach conducts by encrypting each compressed secret message bit with the most significant bit of the red channel and then saving the output bit (hidden bit) in the least significant bit of the (green/blue) channel according to the row value (odd/ even). To further security, the suggested approach uses multi-level encryption; employs RSA to encrypt the secret message before applying the Huffman compression and encrypting the hidden bit by (XOR/XNOR) in the embedding method based on the row value of the pixel. Meanwhile, it is planned to use the Huffman coding technique to shorten the length of the encrypted message that will be inserted in the cover image. For the color photos in this work, the standard images were acquired from a standard dataset (USC-SIPI). The suggested approach performs better when measured in terms of mean square error (MSE), peak signal-to-noise ratio (PSNR), and comparison to findings from related prior efforts.

Image colorization is a process where each pixel in images or videos is given a suitable amount of red, green, and blue (RGB) main color components in order to make it appear more vivid. The process of colorization has significant values while preserving historical documentaries or investigating cosmological photography. However, the colorization of historically significant documentaries requires real witnesses, and a significant amount of human labor is needed to colorize even a single image frame. Recently, deep learning-based approaches have become one of the most reliable techniques to automate challenging computer vision tasks. Various deep learning methods are applied to automate the colorization process. However, we have found that most of the colorization models show poor performance while colorizing Bangladeshi historical documentaries. In our work, we developed ColorNet: a deep learning-based model using an encoder and a pre-trained feature extractor named InceptionV3, also, a fusion layer and a decoder. We have built a new dataset from Bangladeshi historical documentaries. After training our colorization model, it shows a significant result while colorizing Bangladeshi historical documentaries.KeywordsColorizationEncoder networkDecoder networkFusion network

In this work, we propose a steganographic scheme for embedding secret message in VQ-compressed images, which aims to achieve high embedding capacity while keeping distortion low. To achieve these objectives, we develop a progressive exponential clustering (PEC) algorithm for partitioning the VQ codebook into a set of clusters. To embed the secret message based on the clustering, we substitute the indexes of the codewords with others within the same cluster according to the size of the cluster and the secret message bits.

Image analysis algorithm was developed to provide the classification parameters for defect of yellow apple fruits. The objectives of this work are: 1) To use and test an image processing system which could classify defects on apple surfaces based on color analysis,and2) Extraction of values of Red, Green and Blue (RGB) coordinates and color properties of Hue, Saturation, and Intensity (HSI) from the infected area. Experimental setup of color analysis was used for taking an image for each apple sample to find and identify apple defect. The results indicated the following points: (1) The value of red color component was decreased (162 - 73.4), (170.4 - 104.4), (210.8 - 98.4), and (202.6 - 113.1 values), and the value of green color component was decreased (148.6 - 73.5), (122.2 - 61.2), (181 - 62.4), and (180.1 - 90.3 values). Meanwhile, the blue color component value changed a little, it is ranged (61.6- 61.9), (61.1- 63.4), (61.4- 62.0), and (61.6- 62.7 values), for color, fungi, bruises and operation defects (which classified into four subclasses of each defect), respectively., (2) The value of red color component was decreased (134.6 - 84.4), (203 - 186.6), (143.8 - 98.4), and (202.8 - 174.9 values), and the value of green color component was decreased (100 - 75.2), (131.4 - 118.), (115.4 - 61.4), and (184.8 - 154.6 values), respectively. Meanwhile, the blue color component value changed a little, it is ranged (62.1- 66.8), (61.6- 62.0), (61.4- 63.4), and (62.4- 62.6 values) for insect, scare, mechanical and russet defects of apple fruit (which classified into three subclasses of each defect), respectively., (3) The value of color component (R,G and B) and color properties (H, S and I) were very important to classify defect of apple fruit., (4) Using of image analysis method in estimation of apple defects, to develop of a sorting system for sorting of apples fruit based on color analysis., and (5) Establishment measuring standard for defects of apple fruits according to image processing technique.

A high capacity reversible data hiding scheme based on right-left shift

Steganography is a data security technique that used as an effort to secure data. Various techniques and media tested in the steganography technique. One of the classic methods that still today is the Least Significant Bit (LSB) method. As one of the classical methods, this method tested in many technical modification developments and tested on various types of cover media. Various LSB methods that have done always show changes in quality. Therefore, this study conducted tests to try to increase the capacity of the steganography and test the quality degradation that occurred using LSB and some modified LSB methods. The evaluations include calculating the PSNR value, drawing the visual spectrogram, and calculating the BER value. The PSNR evaluation shows that the larger the cover media size used, the smaller the risk of quality degradation, and the bigger the secret message, the greater the noise that will be generated. The evaluation of BER shows that any technique depends on the match between the cover media bits and the secret message bits. Evaluation of the calculation of the maximum steganographic capacity shows that the larger the size of the cover media, the greater the capacity of the secret message that the cover media has.

How to embed more secret message into web page with keeping good imperceptibility simultaneously is a trade-off problem for information hiding schemes. This paper presents a novel web page information hiding method based on three inherent features of current web page's HTML Code matrix. This method firstly exploits chaotic transform to deal with secret message, then embeds each bit of secret message into cover web page according to the random odevity of character amount contained by each row(column) in cover web page's HTML code matrix. Its process is very simple to understand and easy to implement. It can improve the largest embedded capacity (LEC) of cover web page greatly with keeping good imperceptibility at the same time. We test our approach on two test data sets which include 1000 web pages in total. The experiment results show that the max LECs for these two data sets are up to 11291 bits and 13545 bits respectively. The average LECs for two data sets has improvement of 80.2% and 24% more than that of other web page information hiding method .