A method for hiding data in the spatial or IWT domains of images is proposed.Design new edge detection method to estimate same edge intensities for both images.XOR operation is used to embed the message and to improve imperceptibility.Proposed method is robust against textural feature steganalysis. In this paper, we present a novel image steganography algorithm that combines the strengths of edge detection and XOR coding, to conceal a secret message either in the spatial domain or an Integer Wavelet Transform (IWT) based transform domain of the cover image. Edge detection enables the identification of sharp edges in the cover image that when embedding in would cause less degradation to the image quality compared to embedding in a pre-specified set of pixels that do not differentiate between sharp and smooth areas. This is motivated by the fact that the human visual system (HVS) is less sensitive to changes in sharp contrast areas compared to uniform areas of the image. The edge detection method presented here is capable of estimating the exact edge intensities for both the cover and stego images (before and after embedding the message), which is essential when extracting the message. The XOR coding, on the other hand, is a simple, yet effective, process that helps in reducing differences between the cover and stego images. In order to embed three secret message bits, the algorithm requires four bits of the cover image, but due to the coding mechanism, no more than two of the four bits will be changed when producing the stego image. The proposed method utilizes the sharpest regions of the image first and then gradually moves to the less sharp regions. Experimental results demonstrate that the proposed method has achieved better imperceptibility results than other popular steganography methods. Furthermore, when applying a textural feature steganalytic algorithm to differentiate between cover and stego images produced using various embedding rates, the proposed method maintained a good level of security compared to other steganography methods.

A steganography embedding method based on edge identification and XOR coding

An effective image steganography scheme can make a good compromise among embedding capacity, imperceptibility, security and robustness. This paper presents a novel data hiding method based on multidirectional line encoding (MDLE) and integer wavelet transform (IWT). It can get a good result in those indicators simultaneously. The method firstly uses the IWT instead of the DWT to achieve accurate extraction of secret bits. The four wavelet sub-bands are divided into non-overlapping 3 × 3 coefficient blocks which are exploited as embedding regions. Secondly, the MDLE method based on the 3 × 3 block model is proposed. The center coefficient of the block is paired with surrounding coefficients in eight directions to embed n -bit secret data respectively, which improves the utilization of coefficients and ensures the change value of coefficient in one direction not to exceed 2 n − 1 , thereby embedding capacity is increased and good imperceptibility is obtained. Finally, a simple edge detection method is proposed and applied to the low frequency approximation sub-band to embed more secret data in edge blocks in order to further enhance the embedding capacity. The experimental results show that the proposed method is not only superior in terms of embedding capacity and image quality than previous methods, but also secure to steganalysis and robust to attacks.

A data hiding scheme based on multidirectional line encoding and integer wavelet transform

Recently, Steganography is an outstanding research area which used for data protection from unauthorized access. Steganography is defined as the art and science of covert information in plain sight in various media sources such as text, images, audio, video, network channel etc. so, as to not stimulate any suspicion; while steganalysis is the science of attacking the steganographic system to reveal the secret message. This research clarifies the diverse showing the evaluation factors based on image steganographic algorithms. The effectiveness of a steganographic is rated to three main parameters, payload capacity, image quality measure and security measure. This study is focused on image steganographic which is most popular in in steganographic branches. Generally, the Least significant bit is major efficient approach utilized to embed the secret message. In addition, this paper has more detail knowledge based on Least significant bit LSB within various Images formats. All metrics are illustrated in this study with arithmetical equations while some important trends are discussed also at the end of the paper.

Performance evaluation measurement of image steganography techniques with analysis of LSB based on variation image formats

Steganography is the discipline of exchanging top secret information by embedding it into a multimedia carrier. The ultimate aim, here is to hide the very existence of the embedded information within seemingly innocuous carriers. The proposed method extracts either Discrete Wavelet Transform (DWT) or Integer Wavelet Transform (IWT) coefficients of both cover image and secret image. After that two extracted coefficient values are embedded by fusion processing technique. Then the stego image is obtained by applying various combinations of DWT and IWT on both images. In this method, we concentrated for perfecting the visual effect of the stego image and robustness against the various attacks by using different wavelet families. Finally performance evaluation is done on dual transform steganography using wavelet families and statistical methods. In our method achieved acceptable imperceptibility and certain robustness.

Dual transform based steganography using wavelet families and statistical methods

Nuclear norm based adapted occlusion dictionary learning for face recognition with occlusion and illumination changes

Steganography is the methods of communicating secrete information hidden in the cover object. The messages hidden in a host data are digital image, video or audio files, etc, and then transmitted secretly to the destination. In this paper we propose Wavelet based Non LSB Steganography (WNLS). The cover image is segmented into 4*4 cells and DWT/IWT is applied on each cell. The 2*2 cell of HH band of DWT/IWT are considered and manipulated with payload bit pairs using identity matrix to generate stego image. The key is used to extract payload bit pairs at the destination. It is observed that the PSNR values are better in the case of IWT compare to DWT for all image formats. The algorithm can’t be detected by existing steganalysis techniques such as chi-square and pair of values techniques. The PSNR values are high in the case of raw images compared to formatted images.

/pdf/wavelet-based-non-lsb-steganography-2e1g4pnfj5.pdf

Wavelet Based Non LSB Steganography

The Face recognition technique is one of the prominent methods to recognize the person Since face is a unique biometric of the individual and face recognition is the superior identification method This paper proposes a novel method for Face recognition by using features of extended LBP The LBP is applied to each 3×3 matrix obtained from detected face through Viola-Jones algorithm to get the features The Face image is rotated for 15 different angles and LBP Features are taken, then SVM is used for classification for FERET and Yale face database The parameters such as FAR, FRR, TSR and EER are measured

Face recognition using extended LBP features and multilevel SVM classifier

/pdf/a-survey-on-secured-and-energy-efficient-hierarchical-1fhaahdzmz.pdf

A Survey on Secured and Energy Efficient Hierarchical Routing Based Protocols for Wireless Sensor Networks

Securing the confidentiality of patient information using the image steganography process has gained more attention in the research community. However, embedding the patient information is a major ...

H. S. Manjunatha Reddy

Papers

Wavelet Based Non LSB Steganography

Face recognition using extended LBP features and multilevel SVM classifier

A Survey on Secured and Energy Efficient Hierarchical Routing Based Protocols for Wireless Sensor Networks

Pixel Prediction-Based Image Steganography Using Crow Search Algorithm-Based Deep Belief Network Approach