Document Analysis And Text Recognition

This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.

Tens of millions of images are captured every day for a variety of applications in almost all domains of human endeavors. We have come to rely on machine learning, including deep learning, to analyze and extract actionable information from captured images via recognizing the presence of patterns of interest. In recent years, these methods, particularly those using deep learning, have exhibited performance levels surpassing human performance in certain applications. The purpose of this book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. To this end, we have assembled original research articles making unique contributions to the theory, methodology, and applications of machine learning in image analysis and pattern recognition.

The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphicalcomponents of a document and to extract information. With ?rst papers dating back to the 1960’s, DAR is a mature but still gr- ing research?eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this ?eld, while broader DAR techniques are nowadays studied and applied to other industrial and o?ce automation systems.

This book constitutes the refereed proceedings of the 15th IAPR International Workshop on Document Analysis Systems, DAS 2022, held in La Rochelle, France, in May 2022.

The four-volume set LNCS 11256, 11257, 11258, and 11259 constitutes the refereed proceedings of the First Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018, held in Guangzhou, China, in November 2018.
The 179 revised full papers presented were carefully reviewed and selected from 399 submissions. The papers have been organized in the following topical sections: