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Detection and Segmentation of Cracks in Weld Images Using ANFIS Classification Method

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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.

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Authors and Affiliations

  1. Department of ECE, Saveetha Engineering College, Chennai, India

    L. Mohana Sundari

  2. Department of ECE, Dr.N.G.P Institute of Technology, Coimbatore, India

    P. Sivakumar

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  1. L. Mohana Sundari
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  2. P. Sivakumar
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Correspondence to P. Sivakumar.

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Mohana Sundari, L., Sivakumar, P. Detection and Segmentation of Cracks in Weld Images Using ANFIS Classification Method. Russ J Nondestruct Test 57, 72–82 (2021). https://doi.org/10.1134/S1061830921300033

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  • DOI: https://doi.org/10.1134/S1061830921300033

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