a review on machine/deep learning techniques for defect/error detection in image processing

The detection of defects is important in quality control in manufacturing. we categorize the defects like electronic components, pipes, welded parts, textile materials, etc. we express artificial visual processing techniques aimed at comprehending the charged picture in a mathematical/analytical manner. recent mainstream and deep-learning techniques in defect detection are studied with their features, stability, and weaknesses explained. we resume with a survey of textural defect detection based on statistical, structural, and other methods. ultimately, we summarize and investigate the application of ultrasonic testing, filtering, deep learning, machine