基于机器视觉的药物自动识别技术

Automatic Drug Recognition Technology Based on Machine Vision

目的基于机器视觉技术对药物图像的识别进行研究,寻找药物识别过程中更优的算法及识别过程中适宜的外部条件。方法通过理论分析结合HALCON软件对药物识别的问题进行一系列实验,分析照明系统和图像处理算法对识别结果的影响。结果研究表明,在成功识别的基础上,识别难度与工作环境有明显的关联,各种处理算法、目标阈值、系统复杂性均可以对识别结果产生明显的影响。结论改进的中值滤波算法与普通的中值滤波算法相比,处理结果得到明显的改善。通过调整外部光源以及背景参照,均对提高处理质量有明显的帮助,通过RGB与HSV阈值处理算法等相关算法的合理结合,系统的识别结果得到明显提高。研究结果可以为药物装配及相关的产业智能化提供重要参考。

The work aims to research the recognition of drug images based on machine vision technology,and seek better algorithms and the appropriate external conditions in the process of drug recognition.Through theoretical analysis combined with HALCON software,a series of experiments were carried out on drug recognition,and the effects of illumination system and image processing algorithms on recognition results were analyzed.The research showed that,on the basis of successful recognition,the recognition difficulty was obviously related to the working environment,and various processing algorithms,target thresholds and system complexity could have a significant impact on the recognition results.Compared with the ordinary median filtering algorithm,the processing results of improved median filtering algorithm are significantly improved.By adjusting the external light source and background reference,it is helpful to improve the processing quality.Through the reasonable combination of RGB and HSV threshold processing algorithms,the recognition result of the system can be significantly improved.The research results can provide important reference for drug assembly and related industrial intelligence.