Abstract

This paper proposes the detection and classifications of weld images for crack detection using image processing techniques. The proposed method consists of preprocessing stage, feature extraction stage, classification stage and crack region segmentation regions. The image enhancement method is used as preprocessing stage and texture and statistical features are extracted from the enhanced weld images. These computed features are then classified into “Excess weld”, “Good weld”, “No weld” and “Undercut weld”, using Adaptive Neuro Fuzzy Inference System (ANFIS) classification method. This proposed method is analyzed in terms of sensitivity, specificity, accuracy, positive predictive value, negative predictive value and precision. The simulation results of the proposed method are compared with other state of the art methods.

中文翻译：

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基于ANFIS分类方法的焊接图像裂纹检测与分割。

摘要

本文提出了使用图像处理技术对裂纹进行检测的焊接图像检测和分类。该方法包括预处理阶段，特征提取阶段，分类阶段和裂纹区域分割区域。图像增强方法用作预处理阶段，并从增强的焊接图像中提取纹理和统计特征。然后，使用自适应神经模糊推理系统（ANFIS）分类方法将这些计算出的特征分为“多余焊缝”，“良好焊缝”，“无焊缝”和“咬边焊缝”。从灵敏度，特异性，准确性，阳性预测值，阴性预测值和精度方面分析了该方法。将该方法的仿真结果与其他现有方法进行了比较。