Journal on Document Analysis and Recognition - Impact Factor

International Journal on Document Analysis and Recognition - Springer | 2024 Impact Factor:2.5 | Cite Score:5.7 | Q1

Impact Factor and Journal Rank of International Journal on Document Analysis and Recognition

About: The International Journal on Document Analysis and Recognition, published by Springer, focuses on advancing the field of computer recognition and analysis of documents. The journal aims to achieve a deep understanding of document content through the recognition of characters, symbols, text, graphics, images, handwriting, signatures, and the automated analysis of document structures.
Key Areas Covered:
The journal addresses various aspects of document analysis, including:
Computer recognition of characters, symbols, text, graphics, images, handwriting, and signatures.
Automated analysis of the physical and logical structures of documents.
Semantic understanding of document content through computational methods.
Research Contributions:
The journal publishes original research, reviews, and methodologies that contribute significant advancements to document analysis and recognition technologies.
Peer Review Process:
All submissions undergo a rigorous peer-review process to ensure high scientific standards and the publication of impactful research.
Impact and Innovation:
Emphasizing innovation, the journal aims to shape the future of document processing technologies and their applications across different fields.
Global Reach and Accessibility:
With a global readership, the journal fosters international collaboration and knowledge exchange in document analysis technologies.
Interdisciplinary Approach:
Encouraging interdisciplinary research, the journal integrates perspectives from computer science, artificial intelligence, image processing, pattern recognition, and document engineering.
Educational and Professional Development:
In addition to research articles, the journal provides educational resources and reviews to support the professional development of researchers and practitioners in document analysis and recognition.

Journal Home: Journal Homepage

Editor-in-Chief: Koichi Kise

Scope: The International Journal on Document Analysis and Recognition publishes articles that focus on computer recognition of characters, symbols, text, lines, graphics, images, handwriting, and signatures, as well as the automatic analysis of the overall physical and logical structures of documents. The ultimate goal is to achieve a high-level understanding of their semantic content. Topics covered include, but are not limited to:
Character and Symbol Recognition:
Techniques and algorithms for recognizing printed and handwritten characters and symbols.
Text and Line Recognition:
Methods for detecting, segmenting, and recognizing text lines, words, and characters in various scripts and fonts.
Image Analysis and Processing:
Image processing techniques for document image enhancement, binarization, noise reduction, and feature extraction.
Handwriting and Signature Recognition:
Approaches to recognizing handwriting styles and signatures, including on-line and off-line methods.
Document Structure Analysis:
Algorithms for analyzing the physical and logical layout of documents, such as page segmentation, text block detection, and layout analysis.
Document Understanding:
Techniques for interpreting the semantic content of documents, including text understanding, document classification, and indexing.
Multimodal Document Analysis:
Integration of multiple modalities, such as text, images, graphics, and audio, for comprehensive document analysis.
Machine Learning and Pattern Recognition:
Application of machine learning, deep learning, and pattern recognition techniques to document analysis tasks.
Document Retrieval and Indexing:
Methods for indexing and retrieving documents based on their content and structure.
Application Areas:
Applications of document analysis and recognition in various domains such as archival, medical, historical, and legal document processing.