基于机器视觉的口服液灯检机关键技术研究

Research on key technology of liquid lamp inspector based on machinevision

设计了一种基于机器视觉的口服液异物检测算法,实现口服液中异物的检测。通过高速工业摄像机获取序列图像,利用二次差分与累积差分法对序列图像进行处理,去除图像中的背景信息,得到只含杂质、少量气泡和部分噪声的灰度图像。通过自适应阈值处理提取运动目标。通过比较异物的大小是否超过医药标准来判断药剂中是否含有异物(比如:毛发、短纤维等),来实现对口服液中可见异物的实时检测。通过实验与现场测试,验证了该检测算法的有效性和可行性。

In this paper, an automatic oral liquid light inspection algorithm is designed to implement the detection of particles in oral liquid. Second-difference and accumulate difference methods are used to remove the background information from the sequence images captured by a high-speed industry camera, and the target images with particles, air bubble and random noise are acquired. Adaptive threshold processing is used to extract moving targets. Real-time detection is completed by determining whether the size of particles, such as hair, fibers and so on, is larger than the pharmaceutical standards. A large number of experimental results show that the proposed algorithm is effective and feasible.