吴世燃,严国平,杨小俊.纸塑复合袋表面缺陷图像分割算法的设计与实现[J].包装工程,2021,42(1):244-249.
WU Shi-ran,YAN Guo-ping,YANG Xiao-jun.Design and Implementation of Image Segmentation Algorithm for Surface Defects of Paper Plastic Composite Bag[J].Packaging Engineering,2021,42(1):244-249. |
| 纸塑复合袋表面缺陷图像分割算法的设计与实现 |
| Design and Implementation of Image Segmentation Algorithm for Surface Defects of Paper Plastic Composite Bag |
| 投稿时间：2020-07-19 |
| DOI：10.19554/j.cnki.1001-3563.2021.01.034 |
| 中文关键词: 纸塑复合袋 边缘检测 区域生长 形状特征 图像分割 |
| 英文关键词: paper plastic composite bag edge detection region growing shape features image segmentation |
| 基金项目:湖北省技术创新专项(重大专项)(2018AAA026);湖北工业大学博士启动基金(BSQD2016003) |
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| 中文摘要: |
| 目的 纸塑复合袋表面缺陷图像受到噪声、光照不均以及自身缺陷等因素的影响，在对图像缺陷区域进行分割时会造成过分割或欠分割。针对此现象提出一种将边缘检测和自适应区域生长法相结合的纸塑复合袋表面缺陷图像的分割算法。方法 首先利用Sobel算子和形态学运算对双边滤波后的缺陷图像进行第1次分割;然后对缺陷区域进行最小外接矩形标记并计算其形状特征，通过判定形状特征大小来决定是否继续分割;最后将符合继续分割的图像缺陷区域质心作为初始种子点，在原始图像上进行自适应区域生长，形成第2次分割结果，完成缺陷图像分割。结果 与其他算法相比，该算法对各类常见缺陷均能取得较好的分割效果，Dice系数均在0.93以上。结论 该算法分割精度较高，有较强的鲁棒性，可以满足工业上的生产需求。 |
| 英文摘要: |
| The surface defect image of paper plastic composite bag surface defect is affected by noise, uneven illumination and the characteristics of the defect itself. It will lead to over segmentation or under segmentation in image defect region segmentation. In view of this phenomenon, a segmentation algorithm of paper plastic composite bag surface defect image which combined edge detection and adaptive region growth method was proposed. Firstly, Sobel operator and morphological operation were used to segment the defect image after bilateral filtering for the first time; then, the minimum circumscribed rectangle was marked on the defect area and its shape feature was calculated, and whether to continue segmentation was determined by determining the size of the shape feature; finally, the centroid of the defect region in the image that conformed to the continuous segmentation was used as the initial seed point to carry out self adaptation on the original image. The second segmentation result was formed by growing the region to complete the defect image segmentation. Compared with other algorithms, this algorithm can achieve better segmentation results for all kinds of common defects, and the Dice coefficients was above 0.93. The algorithm has high segmentation accuracy and strong robustness, which can meet the needs of industrial production. |
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