Sharif Digital Repository

Designers and manufacturers of cryptographic devices are always worried about the vulnerability of their implementations in the presence of power analysis attacks. This article can be categorized into two parts. In the first part, two parameters are proposed to improve the accuracy of the latest hypothetical power consumption model, so-called toggle-count model, which is used in power analysis attacks. Comparison between our proposed model and the toggle-count model demonstrates a great advance, i.e., 16%, in the similarity of hypothetical power values to the corresponding values obtained by an analog simulation. It is supposed that the attacker would be able to build such an accurate power... 

Image registration is an important task in medical image processing. Assuming spatially stationary intensity relation among images, conventional area based algorithms such as CC (Correlation Coefficients) and MI (Mutual Information), show weaker results alongside spatially varying intensity distortion. In this research, a structural representation of images is introduced. It allows us to use simpler similarity metrics in multimodal images which are also robust against the mentioned distortion field. The efficiency of this presentation in non-rigid image registration in the presence of spatial varying distortion field is examined. Experimental results on synthetic and real-world data sets... 

In recent days imaging systems have seen considerable extended usage due to their ease of use and reasonable price. However, they have weaknesses lies in image resolution. In order to increase the quality of the images, due to the technical limitations and costs of hardware parts, software techniques like the super-resolution is used, which means increasing the density of pixels in the image. The super-resolution is broken down into two categories; super-resolution using a single image and super-resolution using multiple images. In this paper, a method for increasing image quality, based on the Dong method has been proposed. In the proposed method, which is based on only one image, tries to... 

Local and global based methods are two main trends for face recognition. Local approaches extract salient features by processing different parts of the image whereas global approaches find a general template for face of each person. Unfortunately, most global approaches work under controlled envi-ronments and they are sensitive to changes in the illumination. On the other hand, local approaches are more robust but finding their optimal parameters is a challenging task. This work proposes a new local-based approach that automatically tunes its parameters. The proposed method incorporates different techniques. In the first step, convolutional neural network (CNN) is employed as a trainable... 

Proposing a proper method for face recognition is still a challenging subject in biometric and computer vision applications. Although some reliable systems were introduced under relatively controlled conditions, their recognition rate is not satisfactory in the general settings. This is especially true when there are variations in pose, illumination, and facial expression. To alleviate these problems, a hybrid face recognition system is proposed which benefits from the superiority of both convolutional neural network (CNN) and support vector machine (SVM). To this end, first a genetic algorithm is employed to find the optimum structure of CNN. Then, the performance of the system is improved... 

Deep neural networks are currently the best solution for road and traffic scene interpretation for autonomous and self-driving vehicles. Compared to the autonomous cars, motorcycles have significant flexibility and advantages in crowded traffic situations and especially in non-urban and off-road areas. Many off-road tracks especially for agriculture and environment management tasks are only traversable with motorcycles. In this paper, a deep neural network is used for design and implementation of the vision system for navigation of an autonomous motorcycle. The proposed framework is evaluated using real world scenarios captured by a real motorcycle in various complex situations. The... 

Face recognition has been an important topic in computer vision for the last two decades. While many algorithms have been developed to address this issue, one of the major challenges faced by them is variation in pose. One of the possible solutions is to find invariant features among different poses of a single person. In this paper a geometry mapping between a frontal face and its rotated pose is used to find invariant features for pose robust face recognition. This mapping is solely based on the angle of rotation and indicates mutual regions between a frontal view of a person and its rotated image. Invariant features based on the low frequency coefficients of these mutual regions are then... 

During the last years several logic styles have been proposed to counteract power analysis attacks. This article starts with a brief review of four different logic styles namely RSL, MDLP, DRSL, and TDPL. This discussion continues to examine the effect of the number of fanouts in power consumption of a CMOS inverter. Moreover, it is shown that insertion of delay elements in typical CMOS circuits is not adequate to prevent the glitches and information leakage unless the fanouts of input signals are balanced. Whereas enable signals have to be classified according to the depth of combinational circuits implemented using pre-charge logic styles, we show that the number of fanouts of enable... 

Several logic styles such as Masked Dual-Rail Pre-charge Logic (MDPL) and Dual-Rail Random Switching Logic (DRSL) have been recently proposed to make implementations resistant against power analysis attacks. In this paper, it is shown that the circuits which contain sequential elements, flip-flops, and implemented in MDPL or DRSL styles are vulnerable to DPA attacks. Based on our results, the information leakage of CMOS D-flip-flops that are used to construct MDPL and DRSL D-flip-fiops is the cause of this vulnerability. To reduce the leakage, a modification on the structure of the MDPL and DRSL flip-flops are proposed; two CMOS D-flip-flops are used in the suggested structure. The proposed... 

Kernel based methods are significantly important in the pattern classification problem, especially when different classes are not linearly separable. In this paper, we propose a new kernel, which is the modified version of the polynomial kernel. The free parameter (d) of the proposed kernel considerably affects the error rate of the classifier. Thus, we present a new algorithm based on the Fisher criterion to find the optimum value of d. Simulation results show that using the proposed kernel for classification leads to satisfactory results. In our simulation in most cases the proposed method outperforms the classification using the polynomial kernel  

Fragile data hiding has been extensively used for secure transmission of the sensitive data using cover images, audios and videos. In the past decade, increasingly the remote sensing applications require transmission and archiving of large number of aerial images and videos. Storage and processing of remote sensing data in the public cloud computing and storage platforms, with servers outside the control of the data owners, requires sufficient attention to persevering the privacy of the data. Furthermore, in the past few years the applications of drones and unmanned aerial vehicles demand algorithms designed especially for low altitude remote sensing data. In this paper, a novel fragile data... 

Community based Question Answering (CQA) websites enable users to post their questions and their questions will be answered by other users. These group of social networking websites are one of the most popular websites on the Internet. The responses on these CQA websites can be for specific questions related to a specific field of interest to the users or to all kind of questions. Creating automated CQA websites is of great interest for the natural language processing research. One of task in development of automated CQA websites is finding similar questions to the question asked by the user. In this paper, a novel method for finding questions relevant questions to the question of a user... 

In the past few years, the application of surveillance for security and smart cities are growing rapidly. The human detection based on the surveillance videos is a complex task and traditional clothing such as headscarf makes this task even more difficult. The surveillance systems designed for many countries are required to be able to recognize the people with these traditional clothing. In this paper, a computer vision system for partially covered face detection in low resolution surveillance videos containing traditional Middle Eastern clothing including the headscarf is presented. The proposed framework uses a combination of Haar cascade and Locally Binary Patterns Histogram (LBPH) for... 

Tourism is one of the largest sources of economic revenue for many countries around the world. The historical and cultural treasures of Iran made it one the main destinations for international tourists. One of the biggest problems encountered by the tourists during the visit to monuments of Iran is the lack of information about the visited landmark. Given that cameras can be found in all of the smart phones, the use of the landmark's photos can be very important for obtaining information about the tourism sites. The detection of the landmarks in an image taken by the mobile phone camera can be a very complex task depending on the angle and the light situation in which the photo is taken. In... 

Fragile data hiding has been extensively used for secure transmission of the sensitive data using cover images, audios and videos. In the past decade, increasingly the remote sensing applications require transmission and archiving of large number of aerial images and videos. Storage and processing of remote sensing data in the public cloud computing and storage platforms, with servers outside the control of the data owners, requires sufficient attention to persevering the privacy of the data. Furthermore, in the past few years the applications of drones and unmanned aerial vehicles demand algorithms designed especially for low altitude remote sensing data. In this paper, a novel fragile data... 

Medical images contain information about vital organic tissues inside of human body and are widely used for diagnoses of disease or for surgical purposes. Due to vital rule of image reconstruction in medical sciences the corresponding algorithms with better efficiency and higher speed is desirable. Most algorithms in image reconstruction are operated on frequency domain such as filtered back projection. In this paper, a Kalman filter technique which is operated in time domain is introduced for reconstruction of CT medical images. Results indicated that as the number of projection increases in both normal collected ray sum and the collected ray sum corrupted by noise the quality of... 

One crucial part of an image registration algorithm is utilization of an appropriate similarity metric. For common similarity metrics such as CC or MI, it is assumed that the intensities of image pixels are independent from each other and stationary. Accepting these assumptions, one will have difficulty doing image registration in the presence of spatially varying intensity distortion. In Myronenko et al. [5] a solution based on minimization of residual complexity is introduced to solve this problem. In this work, the weakness of RC method is investigated for more complex spatially varying intensity distortions and a modification of this method is presented to improve its performance in such... 

Defining a suitable similarity measure is a crucial step in (medical) image registration tasks. A common problem with frequently used intensity-based image registration algorithms is that they assume intensities of different pixels are independent of each other that could lead to low registration performance especially in the presence of spatially-varying intensity distortions, because they ignore the complex interactions between the pixel intensities. Motivated by this problem, in this paper we present a novel similarity measure which takes into account nonstationarity of the pixels intensity and complex spatially varying intensity distortions in mono-modal settings. Experimental results on... 

Multi-agent robotic platforms are increasingly used for various commercial applications. In this paper, a cross altitude visual analytic framework for a group of robots, singularly referred to as MOdular RApidly Deployable Decision Support Agent (MORAD DSA), used for decision support and various services in the smart city environment is presented. The robotic subsystem consists of two agents operating in different altitudes. These agents give the decision support system the ability to have encompassing view of the operating environment. The visual analytic system which is the focus of this paper uses a deep convolutional neural network to learn the complex patterns required by the urban... 

Visual interpretation of complex visual patterns in non-urban environments is necessary for many applications in smart rural community management, smart farming and smart jungles. In this paper, the Glimpse-Gaze framework for deep learning based visual interpretation of complex rural and jungle environment scenes is proposed. The proposed framework is used for decision support and navigation by a multi-agent robotic system singularly referred to as MOdular RApidly Deployable Decision Support Agent (MORAD DSA). A set of deep con-volutional neural networks are trained for fast and accurate interpretation of jungle scenes. Transfer learning and auxiliary pretraining on salient regions of the...