在食品工业中基于双能量吸收计的无监督异物检测
Vladyslav Andriiashen1, Robert van Liere1,2, Tristan van Leeuwen1,3
1Centrum Wiskunde & Informatica, Science Park 123, 1098 XG Amsterdam, The Netherlands.
Journal of imaging
|July 31, 2024
概括
这项研究引入了一种新的方法,用于使用双能X射线吸收计 (DEXA) 检测食品中的异物. 该技术在识别污染物方面达到95%的准确性,提高了食品安全.
科学领域:
- 食品科学与技术 食品科学与技术
- 图像和传感技术的成像和传感技术
- 质量控制和质量保证
背景情况:
- 射线成像对于农业食品的非破坏性检查至关重要.
- 自主,在线检测异物 (例如,骨头,塑料,金属,虫) 对食品安全至关重要.
- 目前的方法面临着噪音和对比度的挑战,影响检测准确度.
研究的目的:
- 开发一种使用双能X射线吸收计 (DEXA) 对食品产品进行无监督异物检测的方法.
- 为DEXA数据预处理引入一种新的厚度校正模型,以增强异物对比度和细分强度.
- 在肉制品的现实数据集上验证拟议的方法.
主要方法:
- 使用双能X射线吸收计 (DEXA) 进行X射线成像.
- 开发并应用了一种新的厚度校正模型作为DEXA数据的预处理步骤.
- 实现了一个无监督的异物检测算法.
- 在488个来自输送带的肉制品样本上测试了该方法.
主要成果:
- 厚度校正模型有效地使食品产品区域均化,并增强了异物对比度.
- 没有外来物体的样本在97%的案例中被正确识别.
- 检测外来物体的整体准确性达到了95%.
结论:
- 提出的基于DEXA的方法与厚度校正是有效的无监督的外来物体检测在食品中.
- 该技术为食品行业的在线质量控制提供了强大而准确的解决方案.
- 这种方法显著提高了在肉制品中检测污染物的可靠性.
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