Abstract: In order to realize the automatic and intelligent reading  of the precipitation value of Sodium Dodecyl Sulfate (SDS), an automatic image recognition system was designed in a shaking machine for SDS precipitate value automatic determination. After the feasibility analysis of three image processing methods, an image recognition method based on label comparison was selected. This method included two modules such as  image preprocessing and volume value conversion. The main steps included converting RGB to HSV, multichannel binarization, extracting label and precipitate value foreground, finding label and precipitate value contour, etc. It could process multiple test tubes at the same time and give the volume of each tube. The experimental results showed that the average recognition accuracy was 98.945%. Since the image processing light source was fixed, compared with manual reading of indicator values, it not only improved the experimental efficiency, but also reduced the subjective human interference caused by different lines of sight each time reading indicator values, effectively improved the accuracy and realized the automation and intelligence of reading precipitation values.

Key words: wheat, Sodium Dodecyl Sulfate precipitation value, image recognition, volume value conversion, label

摘要： 为实现十二烷基硫酸钠(Sodium Dodecyl Sulfate,SDS)沉淀值读取的自动化、智能化，在SDS沉淀值自动化测定摇床上，设计一种图像自动识别沉淀值系统。通过对3种图像处理方法的可行性分析后，选定一种基于标签比对的图像识别方法。该方法包含图像前处理和体积值转换两大模块，主要步骤包括RGB转换成HSV、多通道二值化、提取标签和沉淀值前景，找标签和沉淀值轮廓等。该方法可以同时处理多个试管，并给出每个试管的体积。试验结果表明，平均识别准确率为98.945%。因图像处理光源固定，相对于人工读取示值，不仅提高试验效率，也降低每次读取示值时，因视线不同而造成的主观人为干扰，有效提高准确性，实现沉淀值读取的自动化与智能化。

关键词: 小麦, 十二烷基硫酸钠沉淀值, 图像识别, 体积值转换, 标签