ME ECE Student, UIET

Glass defects which result into poor quality are a major reason of embarrassment for manufacturers. It is an extremely tedious process to manually inspect very large size glasses. The manual inspection process is slow, time-consuming and prone to human error. Automatic inspection systems using image processing can overcome many of these disadvantages and offer manufacturers an opportunity to significantly improve quality and reduce costs. In this paper we propose an evaluation system for detection of various glass defects like scratches, inclusions, surface defects etc. The process involves the color space selection and a segmentation technique often used in medical imaging has been tested for detection of various defects in glass. The color space conversion helps in the selection of best color space for quantifying the visibility of the defects while the segmentation algorithm involves the use of contour method based on intensity inhomogeneities