在电池的生产过程中,不可避免地会生产出一些次品,因此有必要依托信息技术设计出一套合理的算法来自动完成不合格次品的检出。 利用图像采集设备采集纽扣电池表面图像,对采集的图像依次进行混合噪声滤除、OSTU 最佳阈值分割、图像字符定位分割、缺陷模式提取、BP 神经网络缺陷分类,每一步在满足检测精度的前提下,以算法简洁、高效作为衡量标准,为算法移植到生产实践中的实时检测奠定基础。

It will inevitably produce a number of defective goods in the production process of button batteries, so it is necessary to rely on information technology to design a set of reasonable algorithm to automatically detect the unqualified products. We use image acquisition equipment to get the button cell surface image, and then to filter mixture noise, OSTU optimal threshold segmentation, character of image segmentation, extraction of defect mode, BP neural network classification of defects.A measure of standard of the algorithm in each step is simple and efficient, so it can lay the foundation for the algorithm to do real-time detection in production practices under meeting the detect precision in the premise condition.