Resin lens defect detection method based on convolutional neural network

Abstract

The invention discloses a resin lens defect detection method based on a convolutional neural network. The method comprises the following steps: acquiring an image of a resin lens with defects; carrying out gradient sharpening and median filtering on the image to enhance detail information of the image; marking the position and category of the defect, and making a data set; constructing a convolutional neural network model, wherein the network model is based on an improved DarkNet53 as a backbone network, a multi-scale feature fused neck network and a multi-classification regression network as a detection head; inputting the data set into the network model for training; and inputting a to-be-detected picture into the trained network model for detection, and finally outputting information such as a defect category, a defect position and confidence, namely a final detection result. According to the invention, online detection of the defects of the resin lens can be realized, the generalization performance is good, and the detection efficiency and the detection precision are improved.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a method for detecting defects of resin lenses based on a convolutional neural network. Background technique [0002] Due to its good optical properties, light weight, and low price, resin lenses are the most widely used in the glasses manufacturing industry and are a civilian product with huge demand. During the production process of resin lenses, defects such as pitting, scratches, spots, bubbles, chipping and inclusions may occur. Resin lenses with defects cannot be used because their optical properties are affected by defects. It is necessary to prevent products with defects from flowing into the market and causing greater losses to enterprises. Therefore, it is very necessary to perform defect detection on resin lenses. [0003] At present, the defect detection of resin lenses in the manufacturing industry is still mainly manual, that is, workers use their eyes to observe whe...

AI Technical Summary

Problems solved by technology

This method is not only inefficient and has high labor costs, but also the judgment of defects is seriously affected by the subjective factors of the inspectors, and the accuracy of the inspection cannot be guaranteed.

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