Sharif Digital Repository

in this paper a new method for finding the distance between eyelids, in order to determine the open or closed state of eye, has been introduced. For this aim, first the gray scale image of eye region is converted into a binary image. Next, a differential variance projection function is applied on the binary image of eye region in horizontally direction to show the uppermost and lowest points on the eyelid edges. Having the distance between these two points, the distance between two eyelids will be obtained. This distance may be used as a criterion in recognizing the open or closed state of eye. We have used numerous and different images to evaluate the efficiency of the presented method, and... 

From the birth of multi-spectral imaging techniques, there has been a tendency to consider and process this new type of data as a set of parallel gray-scale images, instead of an ensemble of an n-D realization. However, it has been proved that using vector-based tools leads to a more appropriate understanding of color images and thus more efficient algorithms for processing them. Such tools are able to take into consideration the high correlation of the color components and thus to successfully carry out energy compaction. In this paper, a novel method is proposed to utilize the principal component analysis in the neighborhoods of an image in order to extract the corresponding eigenimages.... 

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... 

This paper presents a new scheme for steganalysis of random LSB embedding, capable of applying to any kind of digital signal in both spatial and transform domains. The proposed scheme is based on defining a space whose elements relate to higher-order statistical properties of the signal and looking for special subsets, which we call Closure of Sets (CoS) in this space. We use this scheme for steganalysis of the LSB steganography in grayscale images, employing a vector of five accurate and monotone features. Experimental results show significantly higher accuracy of the proposed scheme, as compared to those reported in the literature, especially in low embedding rates applications. © 2009... 

We propose a method for steganalysis of still, grayscale images using a novel set of features that are extracted from images. This feature set employs the Gabor filter coefficients to train a multi-layer perceptron neural network and a support vector machine classifier. We show that incorporation of the Gabor filter coefficients to the feature sets of images could have a significant role in discrimination between clean and altered images. Experimental results show that the proposed method outperforms previous methods, introduced for steganalysis of LSB-matching image steganography, in terms of both discrimination accuracy and feature set dimensionality. © 2009 IEEE  

Although Face detection is not a recent activity in the field of image processing, it is still an open area for research. The greatest step in this field is the work reported by Viola and the recent analogous one is proposed by Huang et al. Both of them use similar features and also similar training process. The former is just for detecting upright faces, but the latter can detect multi-view faces in still grayscale images using new features called 'sparse feature'. Finding these features is very time consuming and inefficient by proposed methods. Here, we propose a new approach for finding sparse features using a genetic algorithm system. This method requires less computational cost and... 

In this paper, we propose a new multiresolution watermarking method for still images based on the Contourlet Transform (CT). In our algorithm, the watermark is a grayscale image which is embedded into the host image in its contourlet domain. We demonstrate that in comparison with other methods, the proposed method enables us to embed more amount of data into the host image without degrading its perceptual quality. The experimental results show robustness against several common watermarking attacks such as compression, adding noise, and filtering. ©2009 IEEE  

This paper proposes an image watermarking scheme for copyright protection based on Independent Component Analysis (ICA). In the suggested scheme, embedding is carried out in cumulative form in spatial domain and ICA is used for watermark extraction. For extraction there is no need to access the original image or the watermark, and extraction is carried out only with two watermarked images. Experimental results show that the new method has better quality than famous methods [1], [2], [3] in spatial or frequency domain and is robust against various attacks. Noise addition, resizing, low pass filtering, multiple marks, gray-scale reduction, rotation, JPEG compression, and cropping are some... 

This paper proposes an image watermarking scheme for copyright protection based on Independent Component Analysis (ICA). In the suggested scheme, we divide the original image into blocks and use the ICA to project the image into a basis with its components as statistically independent as possible. The data embedding is carried out in cumulative form in the ICA basis and also the ICA is used for watermark extraction. The extraction process could be either non-blind, through a straightforward procedure, or blind, via a tricky method we propose. Experimental results show that the new method outperforms some well-known image watermarking methods [1], [2], [3] in spatial or frequency domain and... 

We propose a new nonblind multiresolution watermarking method for still images based on the contourlet transform (CT). In our approach, the watermark is a grayscale image which is embedded into the highest frequency subband of the host image in its contourlet domain. We demonstrate that in comparison to other methods, this method enables us to embed more amounts of data into the directional subbands of the host image without degrading its perceptibility. The experimental results show robustness against several common watermarking attacks such as compression, adding noise, filtering, and geometrical transformations. Since the proposed approach can embed considerable payload, while providing... 

This paper utilizes IJA stochastic learning automaton for detecting noise and tuning value of alpha parameter which is used for image sharpening via gas diffusion model. The method has been applied to gray-scale images in an automatic and adaptive fashion. It is shown that the IJA automaton detects noise and can reform it appropriately. It glides the image to find the pattern of noise and replace it by the relevant characteristics of neighborhood to carry out the local restoration. Then, the automaton makes the image sharp with gas diffusion model by learning alpha parameter. The IJA automaton calculates appropriate local value for each pixel. Finally, experiments are presented and... 

A new adaptive steganography method based on image contrast to improve the embedding capacity and imperceptibility of the stego images is presented. The method exploits the average difference between the gray level values of the pixels in 2x2 blocks of non-overlapping spatially and their mean gray level in order to select valid blocks for embedding. The method was tested on different gray scale images. Results show that our proposed approach provides larger embedding capacity, while being less detectable by steganalysis methods such as χ2 attack and machine learning steganalysis systems, as compared to some well-known adaptive and non-adaptive steganography algorithms  

A novel technique based on image processing inspired by the simple assumption for the first time to assess the roughness of nanofibrous mats based on grayscale variations is proposed. The height of a nanofibrous mat in different regions of the surface is simulated by grayscale variations in the image while the relation between grayscale and height is obtained as a linear function. The roughness is obtained by measuring height variations in the surface profile. Statistical roughness parameters of nanofibrous mats are also obtained from direct measurement with roughness profilometry and atomic force microscopy (AFM) for comparison of the roughness of nanofibrous mats between direct measurement... 

A novel technique based on image processing inspired by the simple assumption for the first time to assess the roughness of nanofibrous mats based on grayscale variations is proposed. The height of a nanofibrous mat in different regions of the surface is simulated by grayscale variations in the image while the relation between grayscale and height is obtained as a linear function. The roughness is obtained by measuring height variations in the surface profile. Statistical roughness parameters of nanofibrous mats are also obtained from direct measurement with roughness profilometry and atomic force microscopy (AFM) for comparison of the roughness of nanofibrous mats between direct measurement... 

A novel technique based on image processing inspired by the simple assumption for the first time to assess the roughness of nanofibrous mats based on grayscale variations is proposed. The height of a nanofibrous mat in different regions of the surface is simulated by grayscale variations in the image while the relation between grayscale and height is obtained as a linear function. The roughness is obtained by measuring height variations in the surface profile. Statistical roughness parameters of nanofibrous mats are also obtained from direct measurement with roughness profilometry and atomic force microscopy (AFM) for comparison of the roughness of nanofibrous mats between direct measurement... 

A better performance and consequently the widespread use of polymeric insulators in different parts of the power grid can increase their role in the grid reliability. The accumulation of contamination and housing-erosion are the two most effective factors in undermining the performance of this type of insulators. Therefore, electric utilities need to identify contaminated insulators for washing and cracks in polymeric housing to replace them with healthy specimens. This paper discusses the impact of contamination layer and housing-erosion of polymeric insulators on the partial discharges (PD) at the insulator surface, through RF-PRPD (phase resolved partial discharge) patterns. The existence... 

The colorization of gray-scale images has always been a challenging task in computer vision. Recently, novel approaches have been introduced for unsupervised image translation between two domains using Generative Adversarial Networks (GANs). Since one can consider the gray-scale and colorful images as two separate domains, we propose a two-stage cycle-consistent network architecture to produce convincible images. First, an intermediate image is generated with a relatively uncomplicated objective function at the output. Next, at the second stage, the intermediate image is enhanced via a residual network structure with a more complicated objective function. Furthermore, by employing two... 

This paper introduces a novel method to detect the typical LSB (Least Significant Bit) embedding and the LSB matching steganography methods applied to grayscale images. The proposed method determines the changes made to some selected features extracted from the gray level run length matrix. It is shown that the run length characteristics can significantly be affected by the embedded message bits, so can be employed as a measure that is quite sensitive to the arrangements of the image pixel values. The extracted features are examined by a nonlinear SVM (Support Vector Machine) classifier with quadratic kernel that can distinguish between stego and clean images. Experimental results are given... 

Partial discharge (PD) measurement and identification have great importance to condition monitoring of power transformers. In this paper a new method for recognition of single and multi-source of PD based on extraction of high level image features have been introduced. A database, involving 365 samples of phase-resolved PD (PRPD) data, is developed by measurement carried out on transformer artificial defect models (having different sizes of defect) under a specific applied voltage, to be used for proposed algorithm validation. In the first step, each set of PRPD data is converted into grayscale images to represent different PD defects. Two “image feature extraction” methods, the Local Binary...