基于机器视觉的中药材类别红外光谱检测建模

The Modeling of Infrared Spectral Detection of Traditional Chinese Medicine Categories Based on Machine Vision

中药材是组成中成药的重要原料,由于不同类别中药材药性相差巨大,严格遵循药方添加规定的中药材对于保证药品安全和疗效意义重大。传统的中药材类别检测是依赖一线员工肉眼和经验,存在检测效率低、劳动强度大、误检率高等缺点。利用不同中药材无机元素的化学成分在红外光谱的照射下呈现的光谱特征,建立基于机器视觉的中药材类别红外光谱检测模型,可以提高中成药加工精度和自动化程度。

Chinese herbal medicine is an important raw material of Chinese patent medicine.As the properties of different types of Chinese herbal medicine vary greatly,it is of great significance to strictly follow the provisions of Chinese herbal medicine to ensure the safety and efficacy of drugs.The traditional Chinese herbal medicine category detection relies on the naked eye and experience of front-line employees,which has the shortcomings of low detection efficiency,high labor intensity and high false detection rate.By using the spectral characteristics of different inorganic elements of Chinese medicinal materials under infrared irradiation,the infrared spectral detection model of Chinese medicinal materials based on machine vision can improve the precision and automation of Chinese patent medicine processing.