Sharif Digital Repository

One of the main objectives of all watermarking algorithms is to provide a secure method for detecting all or part of the watermark pattern in case of usual attacks to a watermarked image. In this paper we introduce a method that is suitable for any spatial domain watermarking algorithms, such that, it can provide a measure for the level of robustness when a given watermark is supposed to be embedded in a known host image. In order to increase the robustness of the watermarked image, for a watermark of n bits, we embed it s times. Doing this, the entire image is divided into 16 equal size blocks. For each block the complexity of the sub-image in that block is measured. The number of... 

Segmentation plays an important role in the machine vision field. Extraction of dominant segments with large number of pixels is essential for some applications such as object detection. In this paper, a new approach is proposed for color image segmentation which uses ideas behind the social science and complex networks to find dominant segments. At first, we extract the color and texture information for each pixel of input image. A network that consists of some nodes and edges is constructed based on the extracted information. The idea of community detection in social networks is used to partition a color image into disjoint segments. Community detection means partitioning vertices of a... 

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... 

Capacity is one of the most important parameters in image watermarking. Different works have been done on this subject with different assumptions on image and communication channel. However, there is not a global agreement to estimate watermarking capacity. In this paper, we suggest a method to find the capacity of images based on their complexities. We propose a new method to estimate image complexity based on the concept of Region Of Interest (ROI). Our experiments on 2000 images showed that the proposed measure has the best adoption with watermarking capacity in comparison with other complexity measures. In addition, we propose a new method to calculate capacity using proposed image... 

In image hiding we embed a secret image into a cover image. In order to minimize the distortion of secret image, we presented a novel steganographic method based on content-aware seam carving. In this paper, we propose a new image hiding method in which, the secret image is initially classified based on image complexity measure. Then it is resized to an appropriate smaller size, but for having the important objects of the image in resized image we use seam carving method that resizes an image whereas the important content of it remains. By applying the seam carving, we have an image that is smaller than the original one, and then we hide it in a cover image. Obviously hiding a smaller secret... 

Watermarking is a suitable approach for digital image authentication. Robustness regarding attacks that aim to remove the watermark is one of the most important challenges in watermarking, in general. Several different attacks are reported that aim to make it difficult or impossible for the real owner of the digital watermarked image to extract the watermark. Some of such common attacks are noise addition, compression, scaling, rotation, clipping, cropping, etc. In this paper we address the issue of print and scan attack by introducing a method to model the scanner and printer. Then we will simulate the print and scan attack on the digital images to evaluate its robustness. In addition, we... 

In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation... 

The proliferation of communication system used in and around man-made structures has resulted in growing need to determine the scattering properties of various commonly used building materials at radio frequencies typically used in business and residential environments. This paper describes the calculation of scattered wave by reinforced concrete walls. For these walls is modeled with a grid of straight wire. We used the Method of Moments (MOM) to find the wire currents. The complex images (CI) method is also used to rapidly evaluate spatial-domain Green's functions for the wall. The angular dependence of scattered fields is shown  

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... 

One of the most important parameters in evaluating a watermarking algorithm is its capacity. In fact, capacity has a paradoxical relation with other two important parameters: image quality and robustness. Some works have been done on watermarking capacity and a few on image complexities. Most works on watermarking capacity is based on information theory and the capacity values which are calculated based on these methods are very tolerate. In this paper we propose a new method for calculating image complexity based on Region Of Interest (ROI) concept. After that we analyze three complexity measures named: Image compositional complexity (ICC), Quad tree and ROI method, with three different... 

This paper presents a complexity-based image compression method using neural networks. In this method, different multi-layer perceptron ANNs are used as compressor and de-compressor. Each image is divided into blocks, complexity of each block is computed using complexity measure methods and one network is selected for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability are evaluated and compared together. Selection of a network for each image block is based on its complexity value or the Best-SNR criterion. Best-SNR chooses one of the trained...