# Color Recognition of Transparent Plastic Based on Multi-Wavelength Transmission Spectrum
## 1 Introduction  
Plastic materials play an important role in the modern world, but they also produce a large amount of plastic waste. It is estimated that by 2050, about 12 billion tons of plastic waste will accumulate in landfills and natural environments worldwide [1]. Plastic waste pollution poses imminent threats to the marine environment, food safety, human health and contributes to climate change [2, 3, 4, 5]. From the perspective of environmental and socio-economic sustainability, recycling is the most effective way to solve plastic pollution, and it is the most dynamic area of the plastic industry today. Plastic recycling and utilization can reduce the demand for new plastic raw materials, thus reducing the consumption of resources and energy in the production process [6, 7, 8], which is consistent with the Sustainable Development Goals (SDGs) of the United Nations (UN). Many countries and regions have carried out a lot of practices in waste plastic recycling [9, 10, 11].  
By sorting the plastics of different materials and colors, the utilization rate of plastic and the final product quality can be obviously improved [12], thus material and color recognitions are essential for plastic sorting and recycling. At present, researchers have carried out many studies on material recognition using spectroscopy, machine vision and other methods [13, 14, 15, 16], while there are few studies on color recognition.  
At present, there are two main plastic color recognition methods: manual recognition and machine recognition. The poor working environment of the manual recognition method poses a great threat to human health, and the low recognition efficiency makes it difficult to meet the needs of large-scale and efficient production [17]. Generally, the machine recognition method realizes automatic color recognition by using machine vision, and the method can be divided into two types: one is the traditional machine vision method, in which the color features are extracted based on red-green-blue (RGB), hue saturation value (HSV), hue intensity saturation (HIS) and other color models, and color recognition models are established using traditional machine learning algorithms such as support vector machine and K-nearest neighbor [18; 19; 20]; the other type is deep learning based machine vision method, in which the color recognition models are established using a large number of sample images and deep learning algorithms such as convolutional neural network [21; 22]. The first type is simple to implement, but the accuracy is low and it is difficult to identify the transparent plastics with similar color. The second type has a good performance in distinguishing transparent plastic with similar color, but the deep learning algorithms are complex and require a large amount of training samples and high-performance computing resources, so the application cost is high. In addition, the image acquisition device in the machine recognition method mostly adopts single-wavelength lighting source, and the sample image is obtained by the camera that is located on the same side of the light source. This structure is susceptible to specular reflection interference, resulting in the degradation of image quality and color recognition effect.  
According to the above problems, this paper proposes a color recognition method for transparent plastic based on multi-wavelength transmission spectrum. LEDs with different wavelengths were used as transmission light sources, and the transmission spectrum of the transparent plastic was obtained at each transmission light wavelength. The ratios of the R, G and B wavebands of each transmission spectrum were used to set up a color feature for color recognition. A color recognition model was established based on the color features and naive Bayes model, realizing the accurate color recognition of transparent plastics with similar color.