List of Articles matching

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  1 - Presenting an Improved Approach in order to Optimum Mother Wavelet Identification for Earth Sciences Data Processing
  فرناز قریشی Behzad tokhmechi امین روشندل کاهو حسین احمدی نوبری
  More information can be extracted from signals, using signal transform tools. Among other tools, “wavelet transform” has an increasing fortune because of its good properties. The main issue is that choosing “different mother wavelet functions” results in diverse conclus More

  More information can be extracted from signals, using signal transform tools. Among other tools, “wavelet transform” has an increasing fortune because of its good properties. The main issue is that choosing “different mother wavelet functions” results in diverse conclusions. There are various algorithms to build a suitable mother wavelet for the analyzed signal. Along with those algorithms, there are procedures too for choosing the optimum mother wavelet among existing functions. From the latter group, the “energy matching” algorithm was used in the present paper to find the optimum mother wavelet. During the use of this algorithm, its deficiency in two aspects was revealed. To solve the problem, “zero mean transform” was chose as an extendable solution to prepare data for the used energy matching algorithm. Applying this simple transform helped us not only finding the optimum mother wavelet but also a unique one. Manuscript profile
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  2 - Remote Sensing Image Registration based on a Geometrical Model Matching
  Zahra Hossein-Nejad Hamed Agahi Azar Mahmoodzadeh
  10.52547/jist.9.36.41
  Remote sensing image registration is the method of aligning two images from the same scene taken under different imaging circumstances containing different times, angles, or sensors. Scale-invariant feature transform (SIFT) is one of the most common matching methods pre More

  Remote sensing image registration is the method of aligning two images from the same scene taken under different imaging circumstances containing different times, angles, or sensors. Scale-invariant feature transform (SIFT) is one of the most common matching methods previously used in the remote sensing image registration. The defects of SIFT are the large number of mismatches and high execution time due to the high dimensions of classical SIFT descriptor. These drawbacks reduce the efficiency of the SIFT algorithm. To enhance the performance of the remote sensing image registration, this paper proposes an approach consisting of three different steps. At first, the keypoints of both reference and second images are extracted using SIFT algorithm. Then, to increase the speed of the algorithm and accuracy of the matching, the SIFT descriptor with the vector length of 64 is used for keypoints description. Finally, a new method has been proposed for the image matching. The proposed matching method is based on calculating the distances of keypoints and their transformed points. Simulation results of applying the proposed method to some standard databases demonstrated the superiority of this approach compared with some other existing methods, according to the root mean square error (RMSE), precision and running time criteria. Manuscript profile
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  3 - 3D Model Reconstruction by Silhouette, Stereo and Motion Features Fusion
  H. Ghassemian H. Ebrahimnezhadi
  In this paper we propose a new approach to reconstruct the three-dimensional model of object using multi camera silhouettes during time. The main idea in this work is to reduce the current bottlenecks of three-dimensional model reconstruction including: ambiguous stereo More

  In this paper we propose a new approach to reconstruct the three-dimensional model of object using multi camera silhouettes during time. The main idea in this work is to reduce the current bottlenecks of three-dimensional model reconstruction including: ambiguous stereo matching in low contrast regions; non-exact color adjustment between cameras which raises the matching uncertainty; shading and non-consistency of intensity duo to motion and varying the light angle which raises the motion estimation error; high dependency of silhouette method to the number of cameras. We propose a novel scheme to combine three popular methods i.e. stereo matching, motion and silhouette. The novelties of this work include: region growing for low color different neighborhood to increase the quality of background removing process, robust feature based stereo matching of multi camera images to find the exact place of some sparse singular points belong to the surface of object, singular points matching to robustly estimate the motion parameters in next frame. Also, we propose a hierarchical cone intersection method to extract the bounding edges visual hull from all the silhouettes captured by virtual cameras during time. Manuscript profile
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  4 - Optimum Design of Branch-Line Couplers with Impedance Matching
  H. Horaizi J. Hamedfar
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  5 - Robust and Fast Aerial and Satellite Image Matching based on Selective Scale and Rotation
  M. Safdari P. Moallem M. Sattari
  SIFT method is used to extract keypoints of the image in order to overcome the problems of matching between the satellite and aerial images, including: difference in scale, rotation, brightness intensity and the geometric shape. Unfortunately, SIFT method extracts sever More

  SIFT method is used to extract keypoints of the image in order to overcome the problems of matching between the satellite and aerial images, including: difference in scale, rotation, brightness intensity and the geometric shape. Unfortunately, SIFT method extracts several unfavorable keypoints of satellite and aerial images because of the turbulence and the environmental factors which leads to unreliable matching and increasing complexity. In order to improve the quality of the extracted specific areas and the run time of the algorithm, first the edges of the original images are extracted by Sobel operator and thresholding, then by using the SIFT method, keypoints are extracted from the edge image. After extracting keypoints, using the rBREIF method, that have stability dependence with respect to atmospheric turbulence and rotation, descriptor for every point of the extracted points is created. Then by applying the bilateral image matching and the RANSAC method that removes the unfavorable adaptive points, the correct matching between the satellite and aerial images are found using the suggested method. The results of the proposed method on the real images show the superiority of this method in term of the accuracy and speed, compared to the some well-known matching methods such as SIFT. Manuscript profile
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  6 - Increasing Image Quality in Image Steganography Using Genetic Algorithm and Reversible Mapping
  Saeed TorabiTorbati مرتضی خادمی عباس ابراهیمی مقدم
  One of the evaluation methods for image steganography is preserving cover image quality and algorithm imperceptibility. Placing hidden information should be done in such a way that there is minimal change in quality between the cover image and the coded image (stego ima More

  One of the evaluation methods for image steganography is preserving cover image quality and algorithm imperceptibility. Placing hidden information should be done in such a way that there is minimal change in quality between the cover image and the coded image (stego image). The quality of the stego image is mainly influenced by the replacement method and the amount of hidden information or the replacement capacity. This can be treated as an optimization problem and a quality function can be considered for optimization. The variables of this function are the mappings applied to the cover image and the hidden information and location of the information. In the proposed method, by genetic algorithm and using the two concepts of targeted search and aimless search, the appropriate location and state for placement in the least significant bits of the cover image are identified. In this method, hidden information can be extracted completely and without error. This feature is important for management systems and cloud networks that use steganography to store information. Finally, the proposed method is tested and the results are compared with other methods in this field. The proposed method, in addition to maintaining the stego image quality, which is optimized based on PSNR, has also shown good performance in examining histogram and NIQE statistical criteria. Manuscript profile
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  7 - Application of Artificial Intelligence during History matching in One of fractured oil Reservoirs
  ناصر اخلاقی ریاض خراط صدیقه مهدوی
  Nowadays different methods of soft computing to reduce time and calculation content are widely used in oil and gas industry. One of the main applications of these methods is prediction of the results of different processes in oil industry which their estimation with More

  Nowadays different methods of soft computing to reduce time and calculation content are widely used in oil and gas industry. One of the main applications of these methods is prediction of the results of different processes in oil industry which their estimation with usual methods is too difficult and has either no single response or their response finding need more time and cost due to their nonlinear of the related problems. Because of much uncertainty on information which used in simulators, the results of these simulation models may have lot errors so production data (Pressure, Production Rate, Water Oil Ratio (WOR), Gas Oil Ratio (GOR) and etc.) during reservoir life is used to historical accommodation between simulator results and actual data. The main purpose of this study is investigation and feasibility study of a usual method of artificial intelligence in oil industry, which is based on the soft computing. In this study, Artificial Neural Network (ANN) is used to make a predicting model for bottom hole pressure and for one of the fractured oil reservoirs with the seven years history of production. Some unconditional parameters such as fracture porosity, horizontal and vertical fracture permeability, height of matrix and matrix-fracture dual porosity were applied as input data of the networks, and pressure was applied as an output in network making. Applied data in network making is achieved from the 50 runs with simulator. The conclusion of this study showed that predicting model of ANN with error less than 4% and reduces the time of process, has a good ability to history matching. Manuscript profile
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  8 - Application of Artificial Intelligence during History matching in One of fractured oil Reservoirs
  ناصر اخلاقی Reyaz kharata Sedigheh Mahdavi
  Nowadays different methods of soft computing to reduce time and calculation content are widely used in oil and gas industry. One of the main applications of these methods is prediction of the results of different processes in oil industry which their estimation with u More

  Nowadays different methods of soft computing to reduce time and calculation content are widely used in oil and gas industry. One of the main applications of these methods is prediction of the results of different processes in oil industry which their estimation with usual methods is too difficult and has either no single response or their response finding need more time and cost due to their nonlinear of the related problems. Because of much uncertainty on information which used in simulators, the results of these simulation models may have lot errors so production data (Pressure, Production Rate, Water Oil Ratio (WOR), Gas Oil Ratio (GOR) and etc.) during reservoir life is used to historical accommodation between simulator results and actual data. The main purpose of this study is investigation and feasibility study of a usual method of artificial intelligence in oil industry, which is based on the soft computing. In this study, Artificial Neural Network (ANN) is used to make a predicting model for bottom hole pressure and for one of the fractured oil reservoirs with the seven years history of production. Some unconditional parameters such as fracture porosity, horizontal and vertical fracture permeability, height of matrix and matrix-fracture dual porosity were applied as input data of the networks, and pressure was applied as an output in network making. Applied data in network making is achieved from the 50 runs with simulator. The conclusion of this study showed that predicting model of ANN with error less than 4% and reduces the time of process, has a good ability to history matching. Manuscript profile
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  9 - Ontology Matching Based on Maintaining Local Similarity of Information Using Propagation Technique
  NazarMohammad Parsa Asieh Ghanbarpour
  In recent years, ontologies, as one of the most important components of the semantic web, have expanded in various fields. The problem of ontology matching has been raised with the aim of creating a set of mappings between entities of ontologies. This problem is classif More

  In recent years, ontologies, as one of the most important components of the semantic web, have expanded in various fields. The problem of ontology matching has been raised with the aim of creating a set of mappings between entities of ontologies. This problem is classified as an NP-hard problem. Therefore, greedy methods have been proposed to solve it in different ways. Selecting the appropriate lexical, structural and semantic similarity criteria and using an effective combination method to obtain the final mapping is one of the most important challenges of these methods. In this paper, an automatic method of matching ontologies is proposed to provide a one-to-one mapping set. This method detects primary mappings based on a new lexical similarity criterion, which is accordance with the descriptive essence of entities and combining this similarity with semantic similarity obtained from external semantic sources. By locally propagating the score of initial mappings in the class hierarchy graph, structurally matching entities are identified. In this method, property matching is examined in a separate step. In the final step, the mapping filter is applied in order to maintain the consistency of the final mapping set. In the evaluation section, comparing the performance of the lexical similarity measure compared to other proposed textual similarity measures, indicates the efficiency of this measure in the problem of ontology matching. In addition, the results of the proposed matching system compared to the results of the set of participating systems in the OAEI competitions shows this system in the second place and higher than many complex matching systems. Manuscript profile