ZHU Yuanyang1， ZHAO Wenzhu1， LIU Sheng1， GAO Hongwen2
（1. School of Computer Science and Technology， Huaibei Normal University， Huaibei 235000, China；2. College of Environmental Science and Engineering， Tongji University， Shanghai 200092, China）
Abstract： The conventional photoelectric detection system requires complex circuitry and spectroscopic systems as well as specialized personnel for its operation. To replace such a system, a method of measuring turbidity using a camera is proposed by combining the imaging characteristics of a digital camera and the high-speed information processing capability of a computer. Two turbidity measurement devices based on visible and near-infrared (NIR) light cameras and a light source driving circuit with constant light intensity were designed. The RGB data in the turbidity images were acquired using a self-developed image processing software and converted to the CIE Lab color space. Based on the relationship between the luminance, chromatic aberration, and turbidity, the turbidity detection models for luminance and chromatic aberration of visible and NIR light devices exhibiting values from 0-1 000 NTU, less than 100 NTU, and more than 100 NTU were established. By comparing and analyzing the proposed models, the two measurement models with the best all-around performance were selected and fused to generate new measurement models. The experimental results prove that the correlation between the three models and the commercial turbidity meter measurements exhibite a significance value higher than 0.999. The error of the fusion model is within 1.05%, with a mean square error of 1.14. The visible light device has less error at low turbidity measurements and is less influenced by the color of the image. The NIR light device is more stable and accurate at full range and high turbidity measurements and is therefore more suitable for such measurements.
Key words： image processing； water quality； turbidity measurement； near-infrared image； color space conversion
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基于可见光和近红外光图像的浊度分析
朱远洋1， 赵文竹1， 刘升1， 郜洪文2
（1. 淮北师范大学 计算机科学与技术学院， 淮北 235000；2. 同济大学 环境科学与工程学院， 上海 200092）
摘要： 传统的光电检测系统需要复杂的电路和分光系统， 以及需要专业人员进行操作。 为了取而代之， 结合数码摄像头的成像特点和计算机的高速信息处理能力， 提出了一种利用摄像头测量浊度的方法。 设计了两种基于可见光和近红外光摄像头的浊度测量装置和一个恒定光强的光源驱动电路。 利用自主开发的图像处理软件获取浊度图像中的RGB数据， 并将其转换为CIE Lab颜色空间。 根据亮度、 色差与浊度之间的关系， 建立了0-1 000 NTU、 小于100 NTU、 大于100 NTU范围内的可见光和近红外装置的亮度和色差的浊度检测模型。 对所提出的模型进行对比分析， 选择综合性能最好的两个测量模型进行融合， 生成了一个新的测量模型。 实验结果表明， 三种模型与商用浊度仪的测量结果之间的相关性均大于0.999， 融合模型的误差在1.05%以内， 均方误差为1.14。 可见光装置在低浊度测量时表现出的误差较小， 受图像颜色影响较小。 近红外装置在全量程和高浊度测量时更稳定、 准确， 更适合此类测量。
关键词： 图像处理； 水质； 浊度测量； 近红外图像； 色彩空间转换
引用格式：ZHU Yuanyang， ZHAO Wenzhu， LIU Sheng， et al. Turbidity analysis using visible and near-infrared light images. Journal of Measurement Science and Instrumentation, 2021, 12（1）： 27-35. DOI： 10．3969／j．issn．1674-8042．2021．01．004
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