Evaluation of human perception of degradation in document images
Large degradations in document images impede their readability as well as substantially deteriorating the performance of automated document processing systems. Image quality metrics have been defined to correlate with OCR accuracy. However, this does not always correlate with human perception of image quality. When enhancing document images with the goal of improving readability, it is important to understand human perception of quality. The goal of this work is to evaluate human perception of degradation and correlate it to known degradation parameters and existing image quality metrics. The information captured enables the learning and estimation of human perception of document image quality. © 2009 Copyright SPIE - The International Society for Optical Engineering.
Document degradation models, Document image analysis, Image quality, Machine learning
Obafemi-Ajayi, Tayo, Gady Agam, and Ophir Frieder. "Evaluation of human perception of degradation in document images." In Document Recognition and Retrieval XVII, vol. 7534, p. 75340T. International Society for Optics and Photonics, 2010.
Proceedings of SPIE - The International Society for Optical Engineering