Online Monitoring of Green Pellet Size Distribution in Haze-Degraded Images Based on VGG16-LU-Net and Haze Judgment
Online Monitoring of Green Pellet Size Distribution in Haze-Degraded Images Based on VGG16-LU-Net and Haze Judgment
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DOI：
10.1109/tim.2021.3052018
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发表时间：
2021-01-01
影响因子：
5.6
通讯作者：
Liu, Xiaoyan
中科院分区：
文献类型：
--
作者：
Duan, Jiaxu;Liu, Xiaoyan
绿色球团矿粒度分布的在线监测是球团生产过程产品质量控制的一项重要工作。传统上，图像分割技术是基于计算机视觉的PSD监测的首要步骤。然而，雾度、颗粒重叠和不均匀的照明导致了严重损害分割性能和PSD测量精度的主要挑战。提出了一种基于K均值聚类的雾度判断模块、融合非权值VGG 16特征的轻量级U网分割模型（VGG 16-LUnet）和用于粘连颗粒分离和轮廓拟合的凸包检测和椭圆拟合模型的全自动在线PSD监测方法。VGG 16-LUnet模型可以在雾霾判断模块的帮助下，从有雾霾和无雾霾的图像中准确地分割出颗粒。因此，该模型可以称为VGG 16-LUnet-TAdj。然后，轮廓拟合模型应用于确定基于分割结果的颗粒尺寸，以及获得PSD。大量的实验上的分割原位捕获的绿色颗粒图像和相应的PSD曲线表明，我们所提出的方法执行可比的，甚至有利于国家的最先进的方法。
Online monitoring of pellet size distribution (PSD) of green pellets is an important work in product quality control of pelletization process. Conventionally, image segmentation technique is a preliminary step in computer vision-based PSD monitoring. However, haze, pellets overlapping, and uneven illumination contribute to the main challenges that severely impair the segmentation performance and PSD measurement accuracy. This article proposed a fully automatic online PSD monitoring method incorporating a K-means clustering-based haze judgment module, a lightweight U-net segmentation model with the fusion of none-weight VGG16 features (VGG16-LUnet), and a convex-hull detection and ellipse fitting model for adhesive pellet separation and contour fitting. The VGG16-LUnet model can accurately segment the pellets from both hazy and haze-free images with the help of haze judgment module. Thus, this model can be called VGG16-LUnet-TAdj. Then, a contour fitting model is applied to determine the pellets sizes based on the segmentation results, and the PSD is obtained as well. Extensive experiments on the segmentation of in situ captured green pellet images and the corresponding PSD curves demonstrate that our proposed method performs comparable or even favorable to the state-of-the-art methods.