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基于视觉注意的V形焊接区域清晰图像获取

陈海永,任亚非,王亚男,曹军旗

陈海永,任亚非,王亚男,曹军旗. 基于视觉注意的V形焊接区域清晰图像获取[J]. 焊接学报, 2018, 39(9): 19-24,35. DOI: 10.12073/j.hjxb.2018390217
引用本文: 陈海永,任亚非,王亚男,曹军旗. 基于视觉注意的V形焊接区域清晰图像获取[J]. 焊接学报, 2018, 39(9): 19-24,35. DOI: 10.12073/j.hjxb.2018390217
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CHEN Haiyong, REN Yafei, WANG Yanan, CAO Junqi. Clear image acquisition of V-shaped welding area based on visual attention[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(9): 19-24,35. DOI: 10.12073/j.hjxb.2018390217
Citation: CHEN Haiyong, REN Yafei, WANG Yanan, CAO Junqi. Clear image acquisition of V-shaped welding area based on visual attention[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(9): 19-24,35. DOI: 10.12073/j.hjxb.2018390217
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基于视觉注意的V形焊接区域清晰图像获取

  • 河北工业大学 控制科学与工程学院, 天津 300130

基金项目: 国家自然科学基金项目（No.61403119）；河北省自然科学基金资助项目（No.F2018202078）；河北省科技计划项目（17211804D）；河北省青年拔尖人才（210003）

Clear image acquisition of V-shaped welding area based on visual attention

  • School of Control Science and Engineering, Hebei University of Technology, Tianjin 300130, China

摘要

    摘要
  • 摘要: 焊接过程中焊接区域亮度范围大，而且随机变化，导致采集的焊缝区域图像干扰大，特征难以提取.文中利用激光条纹良好的方向特性，以及图像中结构光与熔池的亮度特征，提出一种基于视觉注意的焊接区域清晰图像获取方法.针对采集的焊缝区域图像，首先获取在不同检测方向下结构光条纹的单方向特征图，再进行加权融合得到多方向特征图.其次，利用高通巴特沃斯滤波器对原始图像加强，获取亮度特征图.接着提出一种改进的显著性度量方法实现了显著性区域与复杂背景图像区域的较好分割.最后，通过图像融合归一化得出结构光与熔池的清晰图像，并采用聚类中心距离客观评价了图像显著性检测效果.结果表明，试验结果显示提出的方法是有效的.
    Abstract: In the welding process, the welding region has large brightness range and random variation, which result in great disturbance of the weld image and are difficult to extract features. In this paper, a method of obtaining clear image for welding area based on visual attention is proposed by using the directional characteristics of laser fringes and the brightness characteristics of structured light and molten pool in the image. Firstly a unidirectional feature map of structured light fringes under different detection directions is obtained for the weld area image, and the Multi-orientation feature map is obtained by weighted fusion. Secondly, the original image is enhanced by the high-pass Butterworth filter to obtain the intensity feature map. Then, an improved saliency measure method is proposed to realize the good segmentation between the salient region and the complex background image region. Finally, a clear image of structured light and molten pool is obtained by image fusion normalization, and the effect of image saliency detection is evaluated objectively by clustering center distance. The experimental results show that the proposed method is effective.
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    • 参考文献(11)
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  • 收稿日期:  2017-04-05

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