List of Articles بافت

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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 - Door detection based on car vision in outdoor scenes
  abbas vafaei Mehdi Talebi monadjemi monadjemi
  20.1001.1.27170411.1395.8.30.6.8
  Doors are an important sign for blind people and robots to enter and leave the building. Detection of doors in outdoor environments has become one of the most difficult issues in computer vision; Because usually in outdoor doors, the features of a simple door such as ha More

  Doors are an important sign for blind people and robots to enter and leave the building. Detection of doors in outdoor environments has become one of the most difficult issues in computer vision; Because usually in outdoor doors, the features of a simple door such as handles, corners and empty space between the door and the floor are not obvious. In this article, a method for detecting doors in outdoor environments is presented. After extracting the lines and removing the extra lines, the area between the vertical lines is formed and the characteristics of each area including height, width, location, color, texture and number of lines inside the area are extracted. Additional knowledge such as the presence of the door at the bottom of the image, the reasonable height and width of the door, and the difference in color and texture of the door with the surrounding area are then used to determine the presence of the door. This method has been tested on our eTRIMS image collection and our image collection, including doors of houses, apartments and shops, and the presented results show the superiority of the proposed method over the previous methods. Manuscript profile
• Open Access Article
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  3 - 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