Document Image Quality Assessment: A Survey

Abstract

The rapid emergence of new portable capturing technologies has significantly increased the number and diversity of document images acquired for business and personal applications. The performance of document image processing systems and applications depends directly on the quality of the document images captured. Therefore, estimating the document's image quality is an essential step in the early stages of the document analysis pipeline. This article surveys research on Document Image Quality Assessment (DIQA). We first provide a detailed analysis of both subjective and objective DIQA methods. Subjective methods, including ratings and pair-wise comparison-based approaches, are based on human opinions. Objective methods are based on quantitative measurements, including document modeling and human perception-based methods. Second, we summarize the types and sources of document degradations and techniques used to model degradations. In addition, we thoroughly review two standard measures to characterize document image quality: Optical Character Recognition (OCR)-based and objective human perception-based. Finally, we outline open challenges regarding developing DIQA methods and provide insightful discussion and future research directions for this problem. This survey will become an essential resource for the document analysis research community and serve as a basis for future research.