基于图像识别的铝塑包装材料边缘检测

目的为了提高铝塑类包装材料的边缘检测精度,基于图像识别技术设计一种边缘检测方法。方法介绍Canny边缘检测算法,针对其双阈值选择比较困难、边缘检测精度不高等问题,利用Ostu算法实现高、低阈值的选取。基于FPGA(现场可编程门阵列)和DSP(数字信号处理器)搭建一种图像检测系统,并给出系统框图及FPGA内部结构,即异步FIFO模块、串入并出模块、像素窗口刷新模块、数据处理模块以及配套电路等,并以药品铝塑泡罩包装为例进行实验研究。结果改进的Canny算法在保证处理速度的前提下,所检测图像清晰细致,能够得到完整边缘。结论该方法具有准确度高、稳定可靠、识别速度快等特点,可满足包装过程产品检测要求。

Edge Detection of Aluminum-Plastic Packaging Materials Based on Image Recognition

The work aims to improve the edge detection accuracy of aluminum-plastic packaging materials, and design an edge detection method based on image recognition technology. The Canny edge detection algorithm was introduced. As for such problems as difficult double threshold choice and the low edge detection accuracy, high and low thresholds were selected based on Ostu algorithm. An image detection system was built based on FPGA (field-programmable gate array) and DSP (digital signal processor), and the system block diagram and the FPGA internal structure were given, namely asynchronous FIFO module, serial-in parallel-out module, pixel window refresh module, data processing module and matching circuits etc. The experimental studies were carried on with aluminum-plastic bubble cap drug package as example. The experimental results showed that the improved Canny algorithm could obtain clear and detailed images and complete edges on the premise of ensuring processing speed. This method is characterized by high accuracy, stability, reliability and faster recognition speed, and it can meet the product detection requirements in the packaging process.