Sharif Digital Repository

In this paper a method for extracting keypoints from human brain MR images is proposed. These keypoints are obtained based on curved structures in the brain MR images. In this method, a keypoint is center of a circle which includes circular boundaries in the image and is selected based on gradients of the image. These keypoints and their descriptors are scale and rotation invariant. The proposed method is compared with other well-known methods with repeatability measure and ROC curves. Experimental results show that proposed method performs better than other well-known methods, specially, when deformations are remarkable  

Image matching plays an important role in many aspects of computer vision. Our proposed method is based on Scale Invariant Feature Transform (SIFT) which is one of the popular image matching methods. The main ideas behind our method are removing the excess keypoints, adding oriented patterns to descriptor, and decreasing the size of the descriptors. By doing these changes to SIFT, we would have oriented patterns of keypoints. In addition, the numbers of keypoints have been reduced and the places of keypoints would be selected more accurately, and also the size of the descriptors has been reduced  

Feature extraction is one of the most important steps in processing endoscopic data. The extracted features should be invariant to image scale and rotation to provide a robust matching across a substantial range of affine distortions and changes in 3D space. In this study, a method is proposed on the basis of the dual-tree complex wavelet transform. First, a map is estimated for each scale, and then a Gaussian weighted additive function (GWAF) is determined. Keypoints are selected from local peaks of GWAF. The matching and registration are performed by applying normalized mutual information and our modified iterative closest point. Results are reported in terms of robustness to rotation,... 

Feature extraction is one of the most important steps in processing endoscopic data. The extracted features should be invariant to image scale and rotation to provide a robust matching across a substantial range of affine distortions and changes in 3D space. In this study, a method is proposed on the basis of the dual-tree complex wavelet transform. First, a map is estimated for each scale, and then a Gaussian weighted additive function (GWAF) is determined. Keypoints are selected from local peaks of GWAF. The matching and registration are performed by applying normalized mutual information and our modified iterative closest point. Results are reported in terms of robustness to rotation,... 

Previously it was shown that the most important inclination of the EAS events due to geomagnetic field is the effect over the secondary particles of them and the contribution of the primary is so small [1]. These secondary particles are mostly e± and μ ±, so we limited our study over these particles. It was simulated over 520,000 EAS events with (ON) and without (OFF) geomagnetic field for our site (B0 = 28:1 μT i + 38:4 μT k, h = 1200m a.s.l.). It is observed a quite North-South anisotropy in ON events and a quite random anisotropy in OFF events. This anisotropy is comparable with the recorded results in our site (ALBORZ observatory), but the simulated anisotropy is a little more than the... 

In order to improve the performance of feature-based template matching techniques, several research papers have been published. Real-time applications require the computational complexity of keypoint matching algorithms to be as low as possible. In this paper, we propose a method to improve the keypoint detection stage of feature-based template matching algorithms. Our experiment results show that the proposed method outperforms keypoint matching techniques in terms of speed, keypoint stability and repeatability  

A new method, based on the concepts of matrix analysis as well as the learning capabilities of neural networks, for the analysis of nonlinear trusses under dynamic loading is presented. The method can be applied to static trusses too. While there have been attempts in the past to use neural networks to identify and model different structures based on data measured on structural response directly, the main feature and advantage of this new method is in its capability to model a nonlinear truss by assembling the data collected on the response of its members. The basics of the method are: (1) for each truss member, a neural network is trained to learn and simulate its loadresponse behavior, (2)... 

Open access to transmission networks as well as designing an efficient cost allocation method are the key points that provide free competition for participants in power market. Restructuring in power systems has created new challenges which emphasize the development and fairness of economical criteria such as pricing of different services in market environment. Besides, the charge of network usage is a controversial subject, itself. To address this problem, many methods for transmission line cost allocation have been proposed. Amongst them, MW-Mile methods are based on the extent of use concept. Inability to take various fixed together with variable imposed costs into account can be... 

Lifetime is the most important concern in wireless sensor networks due to limited battery power of sensor nodes. In this paper, we focus on designing an energy-efficient and energy-aware routing algorithm, LLR, to increase the operational lifetime of multi-hop wireless sensor networks in the presence of unreliable communication links. Our proposed protocol utilizes a parameter, Broadcasting Delay, in each node associated with the hop parameters passed by a route request packet to select long lifetime paths in the network. The key point in Broadcasting Delay formulation is that it includes both node and link specific parameters. We use two different scenarios: either the link layer... 

This paper presents analytical part of an investigation on the application of prestressed strips for concrete confinement. In this paper, an analytical model is proposed to predict the compressive stress-strain curve of strapped concrete as a function of the confinement level. The model was calibrated based on the experimental data of compressive tests which were described in part A of this paper. Various parameters are considered in the proposed model including volumetric ratio, yield strength and ultimate strain of confining material, shape of cross section, strength of plain concrete. Three key points were defined on the stress-stress curve of strapped concrete columns and applied in... 

Optimal well placement is a crucial step in efficient reservoir development process which significantly affects the productivity and economical benefits of an oil reservoir. However, it is a complex and challenging problem due to the different engineering, geological and economical variables involved. This leads to a very large number of potential scenarios that must be evaluated using numerical reservoir simulations. The key points in such an optimization process are using a fast function evaluation tool and development of an efficient and robust optimization algorithm that can find good solutions with a minimum required number of function evaluations. This study presents an approach that...