基于机器视觉的瓶装白酒杂质检测
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摘要
介绍了一种基于机器视觉的瓶装白酒杂质检测方法.为了从复杂的视觉图像中提取出微小目标,设计了一种倒置翻转式的检测方式,通过高清数字摄像机获取瓶装酒液的视频序列,采用一种改进的二次差分方法,获取瓶装酒液内可能存在的运动目标.根据气泡和可见异物的形态特征进行分类,判断出酒液中是否含有杂质.实验验证了所提方法的有效性.
A method for detecting bottled liquor impurities based on machine vision was introduced. In order to extract small detection targets from a complex image, an inverted flipping detection method was designed. A high-resolution digital video camera was used to acquire the video sequence of the bottled liquor. After that, an improved second-difference method was utilized to detect possible tiny moving targets in the liquid. Morphological characteristics of the bubbles and visible impurities were used to estimate whether the liquor contains impurities. The experiments demonstrate the effectiveness of the proposed method.
A method for detecting bottled liquor impurities based on machine vision was introduced. In order to extract small detection targets from a complex image, an inverted flipping detection method was designed. A high-resolution digital video camera was used to acquire the video sequence of the bottled liquor. After that, an improved second-difference method was utilized to detect possible tiny moving targets in the liquid. Morphological characteristics of the bubbles and visible impurities were used to estimate whether the liquor contains impurities. The experiments demonstrate the effectiveness of the proposed method.
引文
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[2] 田聪, 王建强. 我国白酒行业发展现状及趋势分析[J]. 北方经济, 2012(Z1): 108.
[3] 宋丽. 白酒中白色絮状悬浮沉淀产生原因及处理方法[J]. 酿酒科技, 2011, 2011: 55.
[4] 陈敏. 白酒包装质量检验创新因素分析[J]. 中国高新区, 2018, 11: 25.
[5] 周博文. 保健酒智能视觉检测机器人技术研究[D]. 长沙: 湖南大学, 2012.
[6] 李子龙, 鲍蓉, 刘伟铭. 基于复模糊逻辑系统的运动目标检测方法[J]. 江苏大学学报: 自然科学版, 2017, 38: 677.
[7] 李若晨, 周刚, 琚生根.一种组合核函数的自适应目标跟踪算法[J]. 四川大学学报: 自然科学版, 2017, 54: 55.
[8] Zhao Y, Zhang Z, Gao Z. A simple and workable moving objects segmentation method [C]// Proceedings of the 46th Electronics in Marine, Elmar International Symposium. [s.l.]: IEEE, 2004.
[9] 张巧芬, 高健. 机器视觉中照明技术的研究进展[J]. 照明工程学报, 2011, 22: 31.
[10] 周博文, 王耀南, 葛继, 等. 基于机器视觉的医药注射剂智能检测系统研究[J]. 机器人, 2009, 31: 53.
[11] 吕俊瑞, 罗学刚, 岐世峰. 基于模糊度量视觉特征的非局部均值去噪[J]. 重庆邮电大学学报: 自然科学版, 2018, 30: 408.
[12] 李秀峰, 苏兰海, 荣慧芳, 等. 改进均值滤波算法及应用研究[J]. 微计算机信息, 2008, 24: 235.
[13] Fan J, Zhu X, Wu L. Automatic model-based semantic object extraction algorithm[J]. IEEE Trans Circuits Syst Vid, 2011, 11: 1073.
[14] Schoepflin T, Chalana V, Haynor D R, et al. Video object tracking with a sequential hierarchy of template deformations[J]. IEEE Trans Circuits Syst Vid, 2011, 11: 1171.
[15] 孙健钧, 赵岩, 王世刚. 基于图像梯度信息强化的SIFT特征匹配算法改进[J]. 吉林大学学报: 理学版, 2018, 56: 82.