基于机器视觉的鲍鱼风味片残次品在线检测方法
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向宇航,男,天津科技大学在读硕士研究生

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Online visual detection method of defective Baoyu-flavor-slices based on mechanical vision
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    摘要:

    目的:解决鲍鱼风味片在生产过程中出现的边缘残损、内部气孔以及皮料厚度不均匀等外观缺陷自动化检测问题。方法:提出了一种基于机器视觉的在线检测方法。利用机械梳理装置将鲍鱼风味片整理成单层阵列排布;采集图像后,选择图像分割、灰度值拉伸、轮廓边缘提取等方法进行图像处理;利用外轮廓圆形度特征完成边缘残损检测,通过测量皮料厚度完成皮厚异常检测,通过计算气孔面积,完成气孔检测。结果:该在线检测方法对边缘完整度缺陷的检出率为100%,皮厚度异常缺陷检出率为100%,气孔缺陷的检出率为98.65%。结论:该方法具有较好的应用性,能够实现鲍鱼风味片残次品的在线检测。

    Abstract:

    Objective: To solve the problem of appearance defects of Baoyu-flavor-slices, such as edge damage, internal porosity and uneven wrapper thickness in the production process. Methods: An on-line detection method based on machine vision was proposed. The Baoyu-Flavor-Slices were arranged into a single layer array by mechanical carding device. After image acquisition, image segmentation, gray value stretching and contour edge extraction were selected for image processing. Edge damage detection was completed by using the feature of outer contour roundness, abnormal wrapper thickness detection was accomplished by measuring wrapper thickness, by calculating the porosity area, the porosity detection was completed. Results: The detection rate of this on-line detection method was 100% on edge integrity defect, 100% on abnormal thickness defect and 98.65% on porosity defect. Conclusion: The method has feasible application and can realize the online detection of defective products of Baoyu-flavor-slices.

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向宇航,周聪玲,王永强.基于机器视觉的鲍鱼风味片残次品在线检测方法[J].食品与机械,2022,(11):95-100.
XIANG Yu-hang, ZHOU Cong-ling, WANG Yong-qiang. Online visual detection method of defective Baoyu-flavor-slices based on mechanical vision[J]. Food & Machinery,2022,(11):95-100.

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  • 在线发布日期: 2022-12-15
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