基于机器视觉的水果分级系统设计

目的为提高水果分级准确度,以苹果分拣为研究对象,基于机器视觉设计一种苹果分级包装系统。方法根据实际分级功能需求,以苹果尺寸作为标准设计一种苹果分级系统的总体方案,包括DSP+ARM控制器、工业相机、传输带、光源等。重点讨论图像处理模块,首先完成图像背景分割;利用中值滤波实现图像平滑处理;采用Canny算子实现图像边缘锐化。在图像处理的基础上,建立苹果分级模型。最后进行实验研究。结果实验结果表明,人工挑选分级和机器识别自动分级的吻合率达到了96.8%,证实了系统的有效性和可行性。结论基于机器视觉的苹果自动分级的准确度已经接近人工挑选的水平,可推广到苹果类水果的自动分级、包装。

Design of Fruit Grading Packaging System Based on Machine Vision

The work aims to design an apple grading packaging system based on machine vision with apple sorting as the research object, in order to improve the accuracy of fruit grading. According to the actual grading function requirements, an overall scheme of apple grading system was designed based on the size of apple, including DSP+ARM controller, industrial camera, transmission belt, light source, etc. By focusing on the image processing module, image background segmentation was firstly completed. Median filter was used to realize image smoothing. Canny operator was used to sharpen image edge. Based on image processing, the apple grading model was established. Finally, an experimental study was carried out. The experimental results showed that the anastomosis rate of grading by manual sorting and automatic recognition reached 96.8%, which proved the effectiveness and feasibility of the system. The accuracy of automatic apple grading based on machine vision is close to the level of manual sorting, which can be extended to the automatic grading and packaging of apple fruits.