| 基于改进梯度幅值的包装缺陷检测算法研究及应用 |
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| 引用本文： | 宋丽梅,徐婧玮,杨燕罡,郭庆华,杨怀栋.基于改进梯度幅值的包装缺陷检测算法研究及应用[J].应用光学,2019,40(4):644-651. |
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| 作者姓名： | 宋丽梅 徐婧玮 杨燕罡 郭庆华 杨怀栋 |
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| 作者单位： | 1.天津工业大学 电气工程与自动化学院 天津市电工电能新技术重点实验室, 天津 300387 |
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| 基金项目： | 国家自然科学基金61078041国家自然科学基金51806150天津市应用基础及前沿计划16JCYBJC15400天津市应用基础及前沿计划15JCYBJC51700天津市应用基础及前沿计划18JCQNJC04400天津大学精密测试技术及仪器国家重点实验室开放基金PIL1603天津市企业科技特派员项目18JCTPJC61700天津市高等学校创新团队培养计划TD13-5036 |
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| 摘 要： | 针对包装质量检测精度易受外界光照影响的问题，在已有基于梯度幅值相似性的缺陷检测算法基础上，将局部二值模式算子引入到该算法中，提出了一种基于改进梯度幅值相似性的缺陷检测算法。该算法利用局部二值模式算子的旋转不变性和灰度不变性的特点，并将其与图像的梯度幅值特征进行融合后用于包装的缺陷检测中，提升了缺陷检测算法对光照的鲁棒性。实验结果表明，相比传统梯度幅值缺陷检测算法，该算法具有更好的抗光照影响能力，并且对于不同光照情况下的包装缺陷，该算法的检测准确率可达96.57%。因而，该算法能够被广泛地用于包装缺陷检测中，提高缺陷检测的精度。
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| 关 键 词： | 缺陷检测 梯度幅值 局部二值模式 图像质量评价 |
| 收稿时间： | 2018-12-07 |
Research and application of package defects detection algorithm based on improved GM |
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| Affiliation: | 1.Key Laboratory of Advanced Electrical Engineering and Energy Technology, School of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China2.School of Mechanical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China3.School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong NSW2500, Australia4.Department of Precision Instrument, Tsinghua University, Beijing 100084, China |
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| Abstract: | Quality inspection of package is vulnerable of illumination. Aiming at this problem, a defects detection algorithm based on the improved gradient magnitude(GM) similarity was proposed. Based on the existing defects detection method by gradient magnitude similarity, the local binary pattern (LBP) operator was integrated into the proposed algorithm.The algorithm utilized the characteristics of rotation invariance and gray scale invariance of LBP operator, and combines them with the gradient magnitude features of the image to be used in the defects detection of packaging, which improves the algorithm robustness to illumination.Experimental results show that the proposed algorithm has better anti-illumination ability in comparison with traditional methods, and under different illumination conditions, the detection accuracy of the proposed can reach 96.57%. Therefore, the proposed algorithm can be widely used in quality inspection of package and improve the defects detection accuracy. |
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