Incorporating 3D sensors into the system results in increased power consumption, larger volumes of data, and physical space. This study was motivated by a desire to obtain real-time volumetric data and study information with multiple 2D cameras. Two cameras were used to measure the dimensions of a rectangular object in real time. The row-column-pixel (R-C-P) method was presented using a 2D camera and three rectangular surfaces at the same distance. The R-C-P method also detects discontinuous edge volume. The relationship between the actual dimension and the dimension output by the R-C-P method is established as the distance gradually increases. The results obtained best illustrated the R-C-P method, providing equations to calculate the rectangular object’s surface area dimensions.

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R-C-P Method: An Autonomous Volume Calculation Method Using Image Processing and Machine Vision

  • MA Muktadir,
  • Sydney Parker,
  • Sun Yi

摘要

Incorporating 3D sensors into the system results in increased power consumption, larger volumes of data, and physical space. This study was motivated by a desire to obtain real-time volumetric data and study information with multiple 2D cameras. Two cameras were used to measure the dimensions of a rectangular object in real time. The row-column-pixel (R-C-P) method was presented using a 2D camera and three rectangular surfaces at the same distance. The R-C-P method also detects discontinuous edge volume. The relationship between the actual dimension and the dimension output by the R-C-P method is established as the distance gradually increases. The results obtained best illustrated the R-C-P method, providing equations to calculate the rectangular object’s surface area dimensions.