The Effect of Book Preconditioning on Page-Turning Success Rate during Automated Book Digitization

The growing popularity of e-books and the adoption of e-book reader devices have increased the need for book digitization. Traditional flatbed scanners are easily accessible and widely available; however, manual scanning of books is tiring, tedious, and time-consuming when the book has many pages. Developing automated book scanning instruments at a low cost can allow more people to efficiently access and execute the book digitization. In this study, we propose a cost-effective book scanner with an automated page-flipping function. Our prototype uses a motorized moving shuttle with a vacuum gripper to hold the page and a fan to ensure the turning of the page in the correct direction and number of times. A Raspberry Pi 4 takes pictures of the left and right sides of the book using two digital cameras. When the picture capturing process is completed, it combines pictures into text-based digital formats such as PDF using OCR technology. In our experiments, we scanned five different books having different page numbers (120−700) with various paper characteristics such as paper size (A4 and A5), paper type (coated vs. uncoated), and paperweight (60−250 g/m 2 ). The results showed that we obtained less than 0.9% error in book scanning when the paperweight was between 60−120 g/m 2 . We achieved the most successful scanning with uncoated paper type, A4, A5 paper size, and 115−125 g/m 2 paperweight. We observed that the unsuccessful page scan rating decreased as the number of scanning repetitions increased. The results also showed that it was challenging to turn the pages of new books without encountering problems unless pages were preconditioned by turning. We concluded that three iterations of preconditioning are necessary for new books to reduce errors in the page-turning process.