王星,刘朝英,宋雪玲,郝存明.基于图像配准的药用玻璃瓶印刷字缺陷检测[J].包装工程,2017,38(21):180-185.
WANG Xing,LIU Chao-ying,SONG Xue-ling,HAO Cun-ming.Printed Word Defect Detection of Medicinal Glass Bottle Based on the Image Registration[J].Packaging Engineering,2017,38(21):180-185. |
| 基于图像配准的药用玻璃瓶印刷字缺陷检测 |
| Printed Word Defect Detection of Medicinal Glass Bottle Based on the Image Registration |
| 投稿时间：2017-04-24 修订日期：2017-11-10 |
| DOI： |
| 中文关键词: SIFT算子 特征点提取 图像匹配 图像配准 药用玻璃瓶 印刷字 缺陷检测 |
| 英文关键词: SIFT algorithm feature point extraction image matching image registration medicinal glass bottles printed words defect detection |
| 基金项目:国家自然科学基金（2016018935） |
|
| 摘要点击次数: |
| 全文下载次数: |
| 中文摘要: |
| 目的 准确检测出药瓶印刷字的缺陷。方法 采用目前流行的SIFT特征点提取算子，选用欧氏距离进行初匹配，RANSAC进行精确匹配。结果 药瓶在传送过程中不管发生怎样变化，都能被检测出其印刷字的缺陷，成功剔除不合格药瓶。结论 实验结果表明该方法能够精确地提取图像特征点，准确地匹配图像特征点对。 |
| 英文摘要: |
| The work aims to accurately detect the defects of printed words on the medicinal glass bottles. The currently popular SIFT feature point extraction operator was adopted. Then, the Euclidean distance was used for the initial matching, and the RANSAC was used for the exact matching. In the transmission process, no matter how the medicinal bottle changed, the defects of the printed words could be detected. Thus, the unqualified medicinal bottles could be successfully removed. The experiment results show that this method can accurately extract the image feature points and match the image feature point pairs. |
|
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |
渝公网安备 50010702501716号