Abstract: The traditional bottle defect inspection algorithm distinguishes and locates defects through edge detection and filtering,greatly affected by bottle illumination,and the rough burr area and defect part of the mouth are bright and difficult to distinguish in the image.As a result,the traditional algorithm requires extremely high precision for detecting thresholds.Therefore,a defect inspection algorithm is proposed based on the Histogram of Oriented Gradients (HOG) feature which has four-linear interpolation.This algorithm combines with the uniformity of the image gray value and the brightness mutation characteristic of the defect.Because of the large gray scale contrast between the defect and the background,the gradient direction histogram can be used to calculate the pixel gray value mutations of the bottle ring.During the statistical process,the gradient amplitude is amplified vertically and suppressed horizontally according to the gradient direction,forming a feature vector suitable for the inspection of bottle defects.The bottle defect detection method is combined with the Support Vector Machine (SVM) for two categories judgment.The experimental results show that the algorithm proposed has a higher accuracy compared with the traditional detection method.

Key words: defects detection, histogram of oriented gradients, linear interpolation, feature vector, support vector machine