  Machine vision and image processing are often used with sensors for situation
awareness in autonomous systems, from industrial robots to self-driving cars.
The 3D depth sensors, such as LiDAR (Light Detection and Ranging), Radar, are
great invention for autonomous systems. Due to the complexity of the setup,
LiDAR may not be suitable for some operational environments, for example, a
space environment. This study was motivated by a desire to get real-time
volumetric and change information with multiple 2D cameras instead of a depth
camera. Two cameras were used to measure the dimensions of a rectangular object
in real-time. The R-C-P (row-column-pixel) method is developed using image
processing and edge detection. In addition to the surface areas, the R-C-P
method also detects discontinuous edges or volumes. Lastly, experimental work
is presented for illustration of the R-C-P method, which provides the equations
for calculating surface area dimensions. Using the equations with given
distance information between the object and the camera, the vision system
provides the dimensions of actual objects.
