Font and function word identification in document recognition
Computer Vision and Image Understanding
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
Font Recognition Based on Global Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Gabor Filter Based Multi-class Classifier for Scanned Document Images
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Style Context with Second-Order Statistics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Style Consistent Classification of Isogenous Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
High-order statistical texture analysis--font recognition applied
Pattern Recognition Letters
Can Fractal Dimension Be Used In Font Classification
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Performance Improvement Techniques for Chinese Character Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
A New Method of Recognizing Chinese Fonts
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Character Independent Font Recognition on a Single Chinese Character
IEEE Transactions on Pattern Analysis and Machine Intelligence
An EMD-based recognition method for Chinese fonts and styles
Pattern Recognition Letters
Font recognition of Chinese character based on multi-scale wavelet
CSECS'06 Proceedings of the 5th WSEAS International Conference on Circuits, Systems, Electronics, Control & Signal Processing
Farsi font recognition based on Sobel-Roberts features
Pattern Recognition Letters
New features using fractal multi-dimensions for generalized Arabic font recognition
Pattern Recognition Letters
Typeface personality traits and their design characteristics
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
A framework towards a multi-modal fingerprinting scheme for multimedia assets
International Journal of Business Information Systems
Unsupervised font reconstruction based on token co-occurrence
Proceedings of the 10th ACM symposium on Document engineering
A robust font recognition using invariant moments
ACOS'06 Proceedings of the 5th WSEAS international conference on Applied computer science
A statistical global feature extraction method for optical font recognition
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
A novel statistical feature extraction method for textual images: Optical font recognition
Expert Systems with Applications: An International Journal
Optical font recognition of chinese characters based on texture features
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
Pattern Recognition Letters
Optical font recognition using conditional random field
Proceedings of the 2013 ACM symposium on Document engineering
Arabic font recognition based on diacritics features
Pattern Recognition
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A new statistical approach based on global typographical features is proposed to the widely neglected problem of font recognition. It aims at the identification of the typeface, weight, slope and size of the text from an image block without any knowledge of the content of that text. The recognition is based on a multivariate Bayesian classifier and operates on a given set of known fonts. The effectiveness of the adopted approach has been experimented on a set of 280 fonts. Font recognition accuracies of about 97 percent were reached on high-quality images. In addition, rates higher than 99.9 percent were obtained for weight and slope detection. Experiments have also shown the system robustness to document language and text content and its sensitivity to text length.