In order to solve the recent defect in garbage classification - including low level of intelligence, low accuracy and high cost of equipment, this paper presents a series of methods in identification and judgment in intelligent garbage classification, including a material identification based on thermal principle and non-destructive laser irradiation, another material identification based on optical diffraction and phase analysis, a profile identification which utilizes a scenery thermal image after PCA and histogram correction, another profile identification which utilizes computer vision with innovated data sets and algorithms. Combining AHP and Bayesian formula, the paper innovates a coupling algorithm which helps to make a comprehensive judgment of the garbage sort, based on the material and profile identification. This paper also proposes a method for real-time space measurement of garbage cans, which based on the characteristics of air as fluid, and analyses the functions of air cleaning and particle disposing. Instead of the single use of garbage image recognition, this paper provides a comprehensive method to judge the garbage sort by material and profile identifications, which greatly enhancing the accuracy and intelligence in garbage classification.
翻译:为了解决最近在垃圾分类方面的缺陷----包括情报水平低、准确度低和设备成本高,本文件介绍了在智能垃圾分类中进行识别和判断的一系列方法,包括基于热原则和非破坏性激光辐照的材料识别、基于光学分解和相片分析的另一种材料识别、利用五氯苯甲醚之后的景色热图像和直方图校正的剖面识别、利用计算机视像与创新数据集和算法的另一种剖面识别、将AHP和Bayesian公式相结合的剖面算法,该文件创新了一种有助于根据材料和剖面识别对垃圾类型作出全面判断的混合算法,本文件还提出了基于空气作为液体的特性的垃圾罐实时空间测量方法,并分析了空气清洁和粒子处置的功能。本文提供了一种综合方法,用材料和剖面识别法来判断垃圾的分类,大大提高了垃圾分类的准确性和情报。