3D电影图案图像的分类使用质谱图的最佳高度进行质量检查
Jaeeun Lee1, Hongseok Choi1, Kyeongmin Yum2
1Department of Artificial Intelligence Convergence, Pukyong National University, 45, Yongso-ro, Nam-gu, Busan 48513, Republic of Korea.
Journal of imaging
|August 25, 2023
概括
一个新的算法检查3D电影图案,将其分类为好或坏. 这种简单的基于直方图的方法在批量生产中实现了高精度的质量控制.
科学领域:
- 材料科学 材料科学 材料科学
- 图像处理 图像处理
- 质量控制 质量控制 质量控制
背景情况:
- 3D片模式是最近的营销发展,需要大规模生产的质量检查.
- 由于3D片模式的新性,现有的检查方法是有限的.
- 好的图案呈现出清晰的轮和高对比度,而糟糕的图案则以低对比度模糊,使视觉评估复杂化.
研究的目的:
- 开发一种简单而准确的算法,用于检查和分类3D电影图案.
- 为了解决新型3D薄膜图案目前检查方法的局限性.
主要方法:
- 开发了一个简单的算法,利用直方图的高度进行模式分类.
- 该方法根据图像分析将模式分为"好"或"坏"类别.
主要成果:
- 拟议的算法实现了99.09%的分类准确性.
- 检查过程在6.64秒的计算时间内完成.
- 性能超越了现有的3D电影模式检查算法.
结论:
- 开发的基于直方图的算法为3D电影模式质量检查提供了准确和高效的解决方案.
- 这种方法适用于大规模生产的质量控制,克服模式特征带来的挑战.
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