Document Analysis And Text Recognition: Benchmarking State-of-the-art Systems

Download or read book Document Analysis And Text Recognition: Benchmarking State-of-the-art Systems written by Margner Volker and published by World Scientific. This book was released on 2018-02-23 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: The compendium presents the latest results of the most prominent competitions held in the field of Document Analysis and d104 Recognition. It includes a description of the participating systems and the underlying methods on one hand and the datasets used together with evaluation metrics on the other hand. This volume also demonstrates with examples, how to organize a competition and how to make it successful. It will be an indispensable handbook to the document image analysis community. Contents: Logical Structure and Segmentation: Logical Structure Extraction from Digitized Books (Antoine Doucet) Handwriting Segmentation (Nikolaos Stamatopoulos, Georgios Louloudis, and Basilis Gatos) Digits and Mathematical Expressions: Handwritten Digit and Digit String Recognition (Markus Diem, Stefan Fiel, and Florian Kleber) Handwritten Mathematical Expressions (Harold Mouchère, Christian Viard-Gaudin, Richard Zanibi, and Utpal Garain) Writer Identification and Signature Verification: Writer Identification (Georgios Louloudis, Nikolaos Stamatopoulos, and Basilis Gatos) Arabic Writer Identification Using AHTID/MW and KHATT Database (Fouad Slimane and Sameh Awaida) Signature Verification: Recent Developments and Perspectives (Muhammad Imran Malik, Sheraz Ahmed, Andreas Dengel, and Marcus Liwicki) d104 Recognition: Handwritten d104 Recognition Competitions With the tranScriptorium Dataset (Joan Andreu Sánchez, Verónica Romero, Alejandro H Toselli, and Enrique Vidal) Multifont and Multisize Low-resolution Arabic d104 Recognition Using APTI Database (Fouad Slimane and Christine Vanoirbeek) Readership: Researchers, academics, professionals and graduate students in pattern recognition/image analysis, neural networks, and innovation/technology. Keywords: Document Analysis;Digitisation;Character Recognition;Mathematical Expression Recognition;Digit Recognition;Arabic Documents;Handwriting Recognition;Performance Evaluation;Benchmarking;CompetitionsReview:0