3D Robot Vision System through 2D Shape Based Matching Using Gaussian Smoothing for Gluing Application

  • Authors

    • Mohamad Haniff Harun
    • Mohd Shahrieel Mohd Aras
    • Mohd Firdaus Mohd Ab Halim
    • Khalil Azha Mohd Annuar
    • Arman Hadi Azahar
    • Muhamad Faizal Yaakub
    • Amar Faiz Zainal Abidin
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.33.28160
  • Correlation, Gaussian Smoothing, Region of Interest, Template Matching, Vision System.

  • This investigation is solely on the adaptation of a vision system algorithm to classify the processes to regulate the decision making related to the tasks and defect’s recognition. These idea stresses on the new method on vision algorithm which is focusing on the shape matching properties to classify defects occur on the product. The problem faced before that the system required to process broad data acquired from the object caused the time and efficiency slightly decrease. The propose defect detection approach combine with Region of Interest, Gaussian smoothing, Correlation and Template Matching are introduced. This application provides high computational savings and results in better recognition rate about 95.14%. The defects occur provides with information of the height which corresponds by the z-coordinate, length which corresponds by the y-coordinate and width which corresponds by the x-coordinate. This data gathered from the proposed system using dual camera for executing the three dimensional transformation.

     

     

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    Haniff Harun, M., Shahrieel Mohd Aras, M., Firdaus Mohd Ab Halim, M., Azha Mohd Annuar, K., Hadi Azahar, A., Faizal Yaakub, M., & Faiz Zainal Abidin, A. (2018). 3D Robot Vision System through 2D Shape Based Matching Using Gaussian Smoothing for Gluing Application. International Journal of Engineering & Technology, 7(4.33), 487-490. https://doi.org/10.14419/ijet.v7i4.33.28160