A new quality assessment and improvement system for print media

Print media collections of considerable size are held by cultural heritage organizations and will soon be subject to digitization activities. However, technical content quality management in digitization workflows strongly relies on human monitoring. This heavy human intervention is cost intensive and time consuming, which makes automization mandatory. In this article, a new automatic quality assessment and improvement system is proposed. The digitized source image and color reference target are extracted from the raw digitized images by an automatic segmentation process. The target is evaluated by a reference-based algorithm. No-reference quality metrics are applied to the source image. Experimental results are provided to illustrate the performance of the proposed system. We show that it features a good performance in the extraction as well as in the quality assessment step compared to the state-of-the-art. The impact of efficient and dedicated quality assessors on the optimization step is extensively documented.