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基于视觉仿生机理的铜带表面缺陷检测

DOI: 10.11834/jig.20110409

Keywords: 缺陷检测,视觉仿生,选择注意,马尔可夫模型

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Abstract:

受神经解剖学和心理学中有关视觉系统研究成果的启发,提出一种基于生物视觉仿生机理的铜带表面缺陷检测模型。该模型首先使用Gaussian金字塔分解和Gabor滤波器提取缺陷图像特征,合成特征显著图,然后模拟自底向上注意机制,分析视网膜中央凹的内容以获取what信息;再根据扫视仿真中访问点的时间顺序序列,即扫描路径,组成where信息流;最后利用离散的可观测马尔可夫模型,根据what信息和where信息调整相应类的单个马尔可夫链的概率,最大化训练样本的似然值,从而实现缺陷的正确分类。实验结果表明,本文算法在表面缺陷检测系统中的可行性及有效性,在多类缺陷分类中达到94.40%的总准确率。

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