A Syringe Needle Eligibility Detection Method Based on BP Neural Network
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Abstract
In order to achieve automatic detection of flip and hook defective needles, a syringe needle eligibility detection method based on BP neural network was proposed. Firstly, there are several preprocessing steps including the needle image de-nosing, needle target segmentation and needles contour extraction. Next, needles feature extraction followed by boundary region invariant moment method and needle edge curvature. Then, the designed BP neural network is trained by the samples of the qualified needles, bent needles, and inverted needles. Finally, the quality of the needle is tested by the trained BP neural network. Through a lot of real needle detection experiment, the proposed method is effective and can be used in actual production.
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