Abstract
Fast size measurement is widely used in many fields, such as airport security inspection, logistics classification and so on. In order to reduce the measurement error and enhance the measurement speed, we design a fast size measurement system based on multiple RGB-D cameras and a main axis calculation mechanism based on the distribution of pointcloud normal vectors (MA-PNV) is proposed. In our algorithm, the pointcloud of the object is acquired through coordinate transformation and background subtraction. After statistical outlier removal, the normal vectors of the pointcloud is obtained by the local surface fitting. Then the main axis is calculated based on MA-PNV and size measurement of the object is accomplished. Experimental evaluation is carried out on objects with different shapes, colors and under different illumination conditions. The results illustrate that our algorithm is effective for fast size measurement.
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