Font and function word identification in document recognition
Computer Vision and Image Understanding
A Survey of Methods and Strategies in Character Segmentation
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
Font Recognition and Contextual Processing for More Accurate Text Recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Multifont Classification Using Typographical Attributes
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
High-order statistical texture analysis--font recognition applied
Pattern Recognition Letters
Journal of Cognitive Neuroscience
MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
Unsupervised font reconstruction based on token co-occurrence
Proceedings of the 10th ACM symposium on Document engineering
| Hi-index | 0.00 |
A search engine for font recognition in very large font databases is presented and evaluated. The search engine analyzes an image of a text line, and responds with the name of the font used when writing the text. After segmenting the input image into single characters, the recognition is mainly based on eigenimages calculated from edge filtered character images. We evaluate the system with printed and scanned text lines and character images. The database used contains 2763 different fonts from the English alphabet. Our evaluation shows that for 99.8 % of the queries, the correct font name is one of the five best matches. Apart from finding fonts in large databases, the search engine can also be used as a pre-processor for Optical Character Recognition.