Online Auto-counting System Of Reinforcing Steel Bar And Study On Its Image Processing Algorithm

The quantificational packing of reinforcing steel bars in steelworks is still staying at a low level. Reinforcing steel bars are counted by labor. This work is so monotony that mistakes always take place and leave trouble to the following business of selling. So developing an automatic system for reinforcing steel bar counting shall meets practical need of steelworks. For the plant's situation is very complicated and special, the attempt of reinforcing steel bar counting based on neither photoelectric sensor nor weight sensor can act on. In this paper, a new method of auto-counting based on digital image processing is brought forward. This method, which counts reinforce steel bars on transmission belt before packing, quite different from that after packing, is significative for the automatization of reinforcing steel bar product line and convenience for producing and selling . According to the condition of plants, a systematic framework of automative counting and dividing steel bars is proposed in the paper. This system is composed of two parts for counting and packing which are linking to each other. The counting part is composed of CCD vidicon, image capture card and industrial computer. The packing part is composed of control cabinet, hydraulic power station, dividing device and packing machine. Aside from the system's scheme, the emphases of this paper are focused on the algorithms of image processing. The images of reinforcing steel bars are divided into two types. One type of images , in which steel bars'cross sections are brightness , are segmented by gray thresholding value , and the other type of images , in which reinforcing steel bars'cross sections are colorful, are segmented by Fisher algorithms. The segmentation results are all binary images. At last, recognition and counting of steel bars'cross sections are achieved by the binary images'matching to template library which contains standard templates and defect templates. In the software, several technologies such as region sampling, multi-template detecting and interval scanning, which greatly improve the speed of processing and solve the real-time problems, are adopted. The technique of template library matching assures veracity of counting. As results show, the scheme for reinforcing steel bar counting based on digital image processing is feasible and effectual.