To satisfy the requirement of quality control in printing and packaging industry, a sheet counting apparatus is developed, which adopts a line-scan camera to image the fringes of sheet stack and is able to provide a real-time and noncontact measurement of their quantity. With a brief introduction of the system architecture, our main work focuses on the sheet counting algorithms. The basic principle is to identify each sheet profile from the 1-D image with a robust ridge strength measurement. First, a multiscale bi-Gaussian ridge likelihood measurement and a ridge-valley descriptor are utilized to improve adjacent objects detection by increasing local contrast around sheet fringes. Then, a sheet recognition scheme, which integrates a peak detection algorithm and the ridge region criteria for verification, is proposed to discriminate true sheets from the obtained ridgeness measure. According to experiments and tests in real production lines, our apparatus can reach a very high measuring accuracy for printing papers or cards with a thickness not <0.2 mm.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.