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The aim of image steganography is to hide data in an image with visual and statistical invisibility. There have been a number of steganography techniques proposed over the past few years. In sequence, the development of these methods has led to an increased interest in steganalysis techniques. Most of the steganalysis methods attempt to estimate cover image statistics. One way to provide a secure steganography method is to disturb the estimation of steganalyzers. The main concern of this paper is to resist against steganalysis methods and utilize a mechanism to securely embed more secret data into an image. We present HYbrid steganographic approach (HYSA), which embeds secret data with... 

The existing powerful steganalyzers can find out the presence of secret information in images with high accuracy. Increasing the embedding capacity of cover images reduces the detection risk of stego images. In this respect, we introduce boosted steganography scheme (BSS) that has a preprocessing stage before applying steganography methods. The goal of BSS is increasing the undetectability of stego images. Due to the dependence of embedding capacity of images to their content, we proposed an ensemble steganalyzer to estimate the embedding capacity of each cover image. Since the content of cover images has less significance in steganography, therefore to have more security, the steganographer... 

An ideal steganographic technique embeds secret information into a carrier cover object with virtually imperceptible modification of the cover object. Steganalysis is a technique to discover the presence of hidden embedded information in a given object. Each steganalysis method is composed of feature extraction and feature classification components. Using features that are more sensitive to information hiding yields higher success in steganalysis. So far, several steganalysis methods have been presented which extract some features from DCT or wavelet coefficients of images. Multi-scale and time-frequency localization of an image is offered by wavelets. However, wavelets are not effective in... 

A novel approach for selecting proper cover images in steganography is presented in this paper. The proposed approach consists of two stages. The first stage is an evolutionary algorithm that extracts the signature of cover images against stego images in the form of fuzzy if-then rules. This algorithm is based on an iterative rule learning approach to construct an accurate fuzzy rule base. The rule base is generated in an incremental way by optimizing one fuzzy rule at a time using an evolutionary algorithm. In the second stage of the proposed approach, the fuzzy rules generated in the first stage are used for selecting suitable cover images for steganography. We applied our approach to some... 

In this paper, we present a new adaptive contourlet-based steganography method that hides secret data in a specific or automatically selected cover image. Our proposed steganography method primarily decomposes the cover image by contourlet transform. Then, every bit of secret data is embedded by increasing or decreasing the value of one coefficient in a block of a contourlet subband. Contourlet coefficients are manipulated relative to their magnitudes to hide the secret data adaptively. In addition to proposing contourlet-based steganography method, this work investigates the effect of cover selection on steganography embedding and steganalysis results. We demonstrate, through the... 

Due to the various contents of images, the stego images produced by a steganography method may have different levels of undetectability against steganalyzers. In other words, a steganography method may cause less detectable statistical artifacts on some images compared to other images. In this paper, we analyze different features of images to find the similarity between proper cover images for each steganography method Similarity between images is modeled in form of fuzzy if-then rules using an evolutionary algorithm. Subsequently for hiding secret data in a cover image, we suggest a reliable steganography method that results in an undetectable stego image against most recently reported... 

The problem of spreading secret data to embed into multiple cover images is called batch steganography and has been theoretically considered recently. Few works have been done in batch steganography, and in all of them, the payload is spread between cover images unwisely. We present the Adaptive batch steganography (ABS) approach and consider embedding capacity as a property of images. ABS is an approach to adaptively spread secret data among multiple cover images based on their embedding capacity. By splitting the payload based on image embedding capacity constraint, embedding can be done more secure than the state when the embedder does not know how much data can be hidden securely in an... 

Mostly the embedding capacity of steganography methods is assessed in non-zero DCT coefficients. Due to unequal distribution of non-zero DCT coefficients in images with different contents, images with the same number of non-zero DCT coefficients may have different actual embedding capacities. This paper introduces embedding capacity as a property of images in the presence of multiple steganalyzers, and discusses a method for computing embedding capacity of cover images. Using the capacity constraint, embedding can be done more secure than the state when the embedder does not know how much data can be hidden securely in an image. In our proposed approach, an ensemble system that uses... 

This paper presents a cover selection steganography method based on introduction of a technique for computing steganography capacity as a property of images. An ensemble system that uses different steganalyzer units, determines the upper bound of embedding rate in a cover image. In this technique, each steganalyzer unit is a combination of multiple steganalyzers with a same type but each one trained to detect stego images with a certain payload. Our proposed method minimizes the risk of detection by selecting a proper cover image that its steganography capacity is sufficient to hide a specific secret data securely. Experimental results demonstrate the efficiency and practicability of the... 

Steganalysis is a technique to detect the presence of hidden embedded information in a given data. Each steganalyzer is composed of feature extraction and feature classification components. Using features that are more sensitive to data hiding yields higher success in steganalysis. The present paper offers a new universal approach to steganalysis that uses statistical moments of contourlet coefficients as features for analysis. A non-linear SVM classifier is used to classify cover and stego images. The effectiveness of the proposed method is demonstrated by extensive experimental investigations. The proposed steganalysis method is compared with two well known steganalyzers against typical... 

The first step of any face processing system is detecting the location in images where faces are present. In this paper we present an upright frontal face detection system based on the multi-resolution analysis of the face. In this method firstly, skin-color information is used to detect skin pixels in color images; then, the skin-region blocks are decomposed into frequency sub-bands using contourlet transform. Features extracted from sub-bands are used to detect face in each block. A multi-layer perceptrone (MLP) neural network was trained to do this classification. To decrease false positive detection we use eyes and lips template matching. These templates achieved by averaging... 

An advantage of steganography, as opposed to other information hiding techniques, is that the embedder can select a cover image that results in the least detectable stego image. In a previously proposed method, a technique based on block texture similarity was introduced where blocks of cover image were replaced with the similar secret image blocks; then indices of secret image blocks were stored in cover image. In this method, the blocks of secret image are compared with blocks of a set of cover images and the image with most similar blocks to those of the secret image is selected as the best candidate to carry the secret image. Using appropriate features for comparing image blocks,... 

In this paper, a new adaptive steganographic scheme based on contourlet transform is presented that provides large embedding capacity. In this method, embedding is done in contourlet transform domain. The contourlet coefficients with larger magnitude that correspond to the edges are selected for embedding. This selection is due to less sensitivity of human eyes to non-smooth regions. Each bit of secret data is embedded by exchanging the value of two coefficients in a 4×4 block of a contourlet subband. The proposed method is examined with two strong steganalysis algorithms and the results show that we could successfully embed data in a cover image with the capacity of 0.05 bits per pixel.... 

Powerful universal steganalyzers were proposed in the literature during the past few years. In addition some studies have been conducted on improvements of current steganalysis results using information fusion techniques, merging available feature vectors, etc. This paper presents two independent ideas, which can be used together, to obtain higher accuracy in detecting stego images. First, we propose the use of boosted fusion methods to aggregate outputs of multiple steganalyzers. Second, we investigate how passing high frequencies through filtering can enhance the results of steganalysis techniques. In this work, it is shown that, through different tests over the state-of-the-art... 

According to the WHO, two individuals die every hour from skin cancer and about 9500 people get skin cancer every day just in the United States. Various computer vision algorithms have been introduced for skin lesion detection, classification, and segmentation. This paper proposes a new segmentation-based algorithm in order to select target components using the persistence diagram of the input images. The results, in comparison with the existing seven different both clustering-and histogram-based segmentation methods using three metrics, show improved performance. Medical image segmentation is an essential task in computer-aided diagnosis. The main improvement of our method is to detect one... 

Inkjet-printing (IJP) technology is recognized as a significant breakthrough in manufacturing high-performance electrochemical energy storage systems. In comparison to conventional fabrication protocols, this printing technique offers various advantages, such as contact-less high-resolution patterning capability; low-cost, controlled material deposition; process simplicity; and compatibility with a variety of substrates. Due to these outstanding merits, significant research efforts have been devoted to utilizing IJP technology in developing electrochemical energy storage devices, particularly in supercapacitors (SCs). These attempts have focused on fabricating the key components of SCs,... 

This work is dedicated to finding a suitable measure to judge thermal performance of nanofluids. The importance of this issue arises from misleading claim of excess heat transfer of nanofluids compared to the base fluid, neglecting the hydraulic effects such as increase in pressure drop. To clarify the issue, the experimental setup with capability to create constant Reynolds number and constant pumping power is constructed. Thermal behavior of nanofluids of silicon oxide/water and aluminum oxide/water and distilled water in developing region of laminar flow regime is investigated. In this regard, the convective heat transfer coefficient within the finned tube heat exchanger is evaluated....