Industrial product counting system based on Faster-RCNN

doi:10.16731/j.cnki.1671-3133.2018.07.021

Abstract

Abstract: There may be missing workpiece and other defects when circular workpieces are packed.To ensure the quality,need to check the number of workpieces in the box.A new auto counting system based on Faster-RCNN is proposed to save labor cost.To handle the problem that the workpiece may be undetected when be sheltered by something,a newly fragmentation training method is proposed.After that,it merges the sub-proposal by horizontal projection and vertical projection and clustering the centroid of the sub-proposals when testing.Realistic experiments prove that the method improves detecting efficiency as well as ensuring very high reliability and compatibility.

Key words: workpiece counting, deep learning, Faster-RCNN, clustering, fragmentation

CLC Number:

TP391

Zhu Zemin, Yu Fangfang, Dong Rong, Li Bo. Industrial product counting system based on Faster-RCNN[J]. Modern Manufacturing Engineering, 2018, 454(7): 124-128.

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