首页> 外文期刊>The International Journal of Advanced Manufacturing Technology >Application of a new image segmentation method to detection of defects in castings
【24h】

Application of a new image segmentation method to detection of defects in castings

机译:一种新的图像分割方法在铸件缺陷检测中的应用

获取原文
获取原文并翻译 | 示例
           

摘要

X-ray-based inspection technique is well applied to identification and evaluation of internal defects in castings, such as cracks, porosities, and foreign inclusions. Combining X-ray inspection with digital image processing and automatic image assessment is now the preferred approach for the continuous inspection of castings. However, in practical application, the quality of the X-ray image is poor. Under the circumstances, many classical thresholding methods usually cannot obtain ideal segmentation results. In this paper, we propose an effective segmentation method for the detection of typical internal defects in castings derived for an X-ray inspection system. The proposed method takes advantage of the fuzzy set theory and bound histogram and presents fuzzy exponential entropy for object and background according to the fuzzy sets and gray-level distribution of the image. The ideal threshold is obtained by maximizing the fuzzy exponential entropy associated with the distribution of the object and background classes in the bound histogram. Experimental results indicate that the proposed method is a powerful method to analyze images derived from X-ray inspection for automatically detecting typical internal defects in castings.
机译:基于X射线的检查技术非常适用于鉴定和评估铸件内部缺陷,例如裂纹,孔隙和异物。现在,将X射线检查与数字图像处理和自动图像评估相结合是连续检查铸件的首选方法。但是,在实际应用中,X射线图像的质量较差。在这种情况下,许多经典阈值方法通常无法获得理想的分割结果。在本文中,我们提出了一种有效的分割方法,用于检测X射线检查系统得出的铸件中典型的内部缺陷。该方法利用模糊集理论和边界直方图的优势,根据图像的模糊集和灰度分布,给出了物体和背景的模糊指数熵。通过最大化与绑定直方图中的对象和背景类别的分布相关的模糊指数熵来获得理想阈值。实验结果表明,该方法是分析X射线检查图像以自动检测铸件中典型内部缺陷的有效方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号