List of Articles Mohammad Javad Dehghani

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  1 - New changes of local binary patterns and classification and segmentation of seabed images
  Babak Goodarzi Javidan Javidan Mohammad Javad Dehghani
  Texture analysis plays an important role in image processing. Considering the extraordinary appearance texture sonar images, texture analysis are good choices for analysis of acoustic seabed images. Local binary pattern (LBP) operator is a very efficient and multi-resol More

  Texture analysis plays an important role in image processing. Considering the extraordinary appearance texture sonar images, texture analysis are good choices for analysis of acoustic seabed images. Local binary pattern (LBP) operator is a very efficient and multi-resolution texture descriptor. It acquires appropriate information from the illumination and moods of images. Despite many developing of the LBP have proposed, but they are sensitive to noise. Also sometimes they lead to describe different structural patterns with same binary codes, which would reduce their ability to differentiate. This paper proposes an overview in provided LBP methods which includes several of the newer ones. Then it proposes a robust framework of binary pattern as completed robust LBP to overcome the inefficiency of all types of LBP which the value of the central pixel replace whit average value of intensity values of 3*3 square adjacent. Proposed approach is a quick tool with high accuracy in the classification of the seabed images. The comparison of simulation results with other known methods indicates the effectiveness of the proposed algorithm. Manuscript profile
• Open Access Article
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  2 - New changes of local binary pattern and classification and segmentation of texture images of the seabed
  Babak Goodarzi Javidan Javidan Mohammad Javad Dehghani
  20.1001.1.27170411.1395.8.27.3.9
  Texture analysis plays an important role in image processing. Due to the highly textured appearance of sonar images, texture analysis methods are a suitable choice for analyzing sea acoustic images. The local binary pattern operator is a very effective multi-resolution More

  Texture analysis plays an important role in image processing. Due to the highly textured appearance of sonar images, texture analysis methods are a suitable choice for analyzing sea acoustic images. The local binary pattern operator is a very effective multi-resolution texture descriptor. This descriptor obtains appropriate information from changing brightness and image states. Although many extensions of local binary pattern have been proposed, existing local binary pattern operators are sensitive to noise. Also, sometimes they lead to the description of different structural patterns with homogeneous binary code, which inevitably reduce their discriminability. This research provides an overview of the local binary pattern method, which includes several of the newer variables. Then, to overcome the inefficiencies of various types of local binary patterns, a robust binary pattern framework called robust local binary pattern is presented, in which the value of each central pixel is replaced by the average gray intensity values ​​of houses from a three by three square. The proposed method is a fast tool with high accuracy in classifying seabed images, and comparing the simulation results with other well-known methods shows the efficiency of the proposed algorithm. Manuscript profile
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  3 - Power Efficient allocation in C-RAN with Multi access technology selection approach
  ALI ASGHAR ANSARI Mohsen Eslami Mohammad Javad Dehghani Saeideh Parsaei Fard
  20.1001.1.27170411.1401.14.53.9.9
  : In this paper, we consider an uplink economy-efficient resource allocation in a multicellular virtual wireless network with a C-RAN architecture where a MNO interacts with a number of MVNOs with a predetermined business model. In each cell of this system, two types of More

  : In this paper, we consider an uplink economy-efficient resource allocation in a multicellular virtual wireless network with a C-RAN architecture where a MNO interacts with a number of MVNOs with a predetermined business model. In each cell of this system, two types of multiple access technologies, namely OFDMA and Massive MIMO, are available for MVNO at two different prices. In this setup, we propose a multi access technology selection approach (MATSA) with the objective to reduce operating costs and maximize the profit of the MVNOs subject to a set of constraints, and formulate this resource allocation problem with the new utility function. Due to the existence of continuous and binary variables in the formulated optimization problem and also the interference between cells in data rate functions, this optimization problem will be non-convex with very high computational complexity. To tackle this problem, by applying the complementary geometric programming (CGP) and the successive convex approximation (SCA), an effective two-step iterative algorithm is developed to convert the optimization problem into two sub problems with the aim to find optimum technology selection and power consumption parameters for each user in two steps, respectively. The simulation results demonstrate that our proposed approach (MATSA) with novel utility function is more efficient than the traditional approach, in terms of increasing total EE and reducing total power consumption. The simulation results illustrate that the profit of the MVNOs is enhanced more than 13% compared to that of the traditional approach. Manuscript profile