Abstract
In this paper, the deep convolutional neural network (DCNN) is applied to locating and recognizing complex workpieces automatically for the vision-based sorting robot in industrial production process. Firstly, in order to obtain the location of workpieces, the pixel projection algorithm (PPA), which consists of pre-procession and pixel projection operation, is presented to eliminate uneven illumination, and locate and segment workpieces images. Then, we get the objective information and identify the object by training DCNN, which is used to recognize the rational degree and type of workpieces at a high rate of speed. Finally, experimental results prove the validity of the location-recognition algorithms for the vision-based sorting robot. The location error and recognition accuracy can be significantly improved in the experimental environment.
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