A Comparative Study of Detection Techniques for Defective Fasteners in Railway Track

Railway track fasteners are critical components ensuring track stability and alignment. Defects in these fasteners, such as missing bolts or broken parts, can compromise railway safety, making early detection essential. This paper presents a comparative study of various image processing techniques to detect defects in railway fasteners by analyzing track images. Techniques evaluated include the variance Projection Method, wavelet Transform, thresholding, Morphological Operations and Connected Component Analysis. These techniques were assessed based on their detection accuracy, computational efficiency, and robustness to variations in lighting and angle. The results provide valuable insights into the most effective image processing techniques for fastener defect detection.