Abstrato

Detection of Defects in Glass Using Edge Detection with Adaptive Histogram Equalization

Nitin kumar, Ranjit kaur

Defects in glass which show poor quality are the major problem for manufacturer in glass making industry. It is very difficult and prone to error process to manually inspect very large size glass. The manual examination process is slow, time consuming and prone to human error. The glass detection technique using image processing provide much relief from error to manufacturer and also provide strength to hold in market providing best quality and low cost glass to customers. In this paper all types of faults are taken. The previous work has been done for only major faults or defects. Detection of defects is based on segmentation using edge detection using gradient approach based on sobel operator. Gray color space and the adaptive histogram technique are used for better contrast and it helps in detection of defects and compares it with the help of structural similarity index (SSIM) parameter with contour detection technique.