基于机器视觉的卷烟爆珠在线检测系统设计

目的：针对卷烟爆珠的质量检测，设计和构建融上料传送、机器视觉图像处理及不合格品剔除功能为一体的卷烟爆珠质量检测系统。方法：通过改进类间方差法对爆珠单颗粒图像进行提取，通过灰度分析、非线性度变换及改进最小外接圆等算法，实现爆珠质量自动化检测，在完成图像自动化检测之后，通过设计的不合格品剔除机构进行剔除，并开展爆珠质量检测的重复试验和应用分析。结果：该系统对不合格爆珠的异色、异行、破损总误检率低于3%，能精确剔除不合格爆珠且系统稳定可靠。结论：基于机器视觉的卷烟爆珠在线检测系统设计，能完成对爆珠质量的自动化在线检测，提高了检测速度与准确度。

Design of on line detection system for cigarette capsules based on machine vision

Objective: At present, mechanical screening method is widely used in cigarette capsules size separation, which has some problems, such as low size detection accuracy, unable to separate different color capsules, leakage capsules and so on. Aiming at the quality detection of cigarette capsules, a quality detection system of cigarette capsules is designed and constructed, which integrates the functions of feeding transmission, machine vision image processing and rejection of unqualified products. Methods: In the detection system, the improved inter class variance method was used to extract the single shot image, and the automatic detection of shot quality was realized by gray analysis, unlimited transformation and improved minimum circumscribed circle algorithm. After the automatic image inspection was completed, and it would be rejected by the designed rejecting mechanism for unqualified products. Results: Through repeated experiments and application analysis, the total false detection rate of diameter or shape or worn capsules of unqualified capsules was less than 3%. It was showed that the proposed method could accurately eliminate unqualified capsules, which verified the feasibility and reliability of the system. Conclusion: The design of online detection system for cigarette capsules based on machine vision can complete the automatic online detection of the quality of the capsules, improve the detection speed and accuracy, and have reference value for improving the competitiveness of the market of the explosive capsules.