IEEE Transactions on Pattern Analysis and Machine Intelligence
Alignment of Free Layout Color Texts for Character Recognition
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Recognition of Indian Multi-oriented and Curved Text
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Proceedings of the International Workshop on Multilingual OCR
Query driven word retrieval in graphical documents
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Multi-oriented Bangla and Devnagari text recognition
Pattern Recognition
Reconstruction of 3d surface and restoration of flat document image from monocular image sequence
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
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In this paper, we present a method of recognizinginclined, rotated characters. First we construct an eigensub-space for each category using the covariance matrixwhich is calculated from a sufficient number of rotatedcharacters. Next, we can obtain a locus by projectingtheir rotated characters onto the eigen sub-space andinterpolating between their projected points. An unknowncharacter is also projected onto the eigen sub-space ofeach category. Then, the verification is carried out bycalculating the distance between the projected point ofthe unknown character and the locus. In our experiment,we obtained quite good results for the CENTURY font of26 capital letters of the English alphabet (A, B, .... ,Z).This method has the added advantage of obtaining therecognition result (category) and angle of inclination atthe same time