An Efficient Technique for Identifying Defects in Stainless Steel (SS) Plate using Image Processing

The process of finding defects in Stainless Steel (SS) plates is tedious. It plays a crucial role in the quality control process. Several industries follow a manual way of checking defects which is time-consuming. Due to this, many industries ‘ output is less efficient, which increases the cost of production. An automated technique for identifying defects in SS plates is discussed here. Edge detection filters like LoG, canny, roberts, perwitt, and sobel were used in the analysis. Parameters such as SSIM (Structural Symmetry Indication Matrix), MSE (Mean Square Error), IEF (Image Enhancement Factor), and PSNR (Peak Signal to Noise Ratio) were calculated. In the analysis, the denoising capacity of the optimized k-Winsorized mean has shown optimal results and was found to be the effective technique for finding defects in SS plates.