An Automated Computer Vision Based System for Bottle Cap Fitting Inspection

Inspection of the cap is one of the most crucial phases of packaging bottles. Defects like loosely fitted cap, scratches/broken cap may occur. It is important to detect these errors as soon as possible. This paper proposes an automated system by which the bottle cap defects can be identified. The bottles with these defects will be rejected by the system. The methods used in this paper are based on computer vision. The system comprises of four methods, which are utilized for bottle cap defect detection: Pattern recognition, Clustering, Object Detection and Line Detection. This paper also presents a comprehensive analysis and a comparison of all the four methods on various parameters. The system has an extensive social and practical value with increasing the productivity, improve the quality of inspection and profitability.