Automated visual inspection of imprint quality of pharmaceutical tablets

Abstract

Visual appearance is an important quality factor of pharmaceutical tablets. Moreover, it plays a key role in identification of tablets, which is needed to prevent mix-ups among various types of tablets. Since identification of tablets is most frequently done by imprints, good imprint quality, a property that makes the imprint readable, is of utmost importance in preventing mix-ups among the tablets. In this paper, we propose a novel method for automated visual inspection of tablets. Besides defect detection, imprint quality inspection is also considered. Performance of the method was evaluated on three different real tablet image databases of imprinted tablets. A “gold standard” was established by manually classifying tablets into a good and a defective class. The receiver operating characteristics (ROC) analysis indicated that the proposed method yields better sensitivity and specificity than the previous defect detection method.