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作 者:周显恩[1] 王耀南[1] 李康军[1] 易国[1] 吴成中[1]
机构地区:[1]湖南大学电气与信息工程学院,长沙410082
出 处:《仪器仪表学报》2015年第9期2021-2029,共9页Chinese Journal of Scientific Instrument
基 金:国家自然科学基金(61175075);国家科技支撑计划(2015BAF11B01)项目资助
摘 要:针对现有啤酒瓶口质量检测中的定位方法在瓶口严重破损或存在大量干扰时定位误差大的问题,提出一种多次随机圆检测及圆拟合度评估的瓶口定位算法。采用阈值分割、重心法和径向扫描获取边缘点,利用从边缘点中随机采样的3个点确定一个圆,定义各边缘点到圆距离小于给定阈值的边缘点的数目与边缘点总数的比值为圆拟合度,提出将圆拟合度作为评估标准搜索最优定位结果的方法,利用多次重复随机圆检测得到大量圆拟合结果并计算对应圆拟合度,以最大圆拟合度对应的圆拟合结果作为瓶口中心。与4种典型方法对比,实验结果表明:在瓶口图像不完整和存在大量干扰时,该方法可实现瓶口高速高精度定位。Aiming at the problem that the existing bottle mouth positioning method for beer bottle mouth quality inspection has large positioning error when serious damages exist on beer bottle mouth or a large amount of interference occurs, a new bottle mouth positioning algorithm called multiple randomized circle detection and fitting degree evaluation is proposed. The threshold segmentation, barycenter method and radial scanning are adopted to capture the edge points. 3 points randomly sampled from all the edge points are used to determine a circle ; the ratio between the number of those edge points with the distances from the edge points to the fitting circle less than a given threshold and the total number of the edge points is defined as the fitting degree of the fitting circle. The method taking the circle fitting degree as the evaluation criteria for searching the best positioning result is proposed. The randomized circle detection is repeated, many circle fitting results are obtained and their corresponding fitting degrees are calculated. The largest fitting degree is found, and the circle center corresponding the fitting circle with the largest fitting degree is regarded as the center of the bottle mouth. The proposed method was compared with 4 popular algorithms. The experiment results show that the proposed method can achieve high speed and accurate positioning of the center of the beer bottle mouth when the bottle mouth images are incomplete or a large amount of interference exists.
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