Optical english font recognition in document images using eigenfaces

Abstract

Introduction: In this paper, a system for recognizing fonts has been designed and implemented. The system is based on the Eigenfaces method. Because font recognition works in conjunction with other methods like Optical Character Recognition (OCR), we used Decapod and OCRopus software as a framework to present the method. Materials and Methods: In our experiments, text typeset with three English fonts (Comic Sans MS, DejaVu Sans Condensed,Times New Roman) have been used. Results and Discussion: The system is tested thoroughly using synthetic and degraded data. The experimental results show that Eigenfaces algorithm is very good at recognizing fonts of synthetic clean data as well as degraded data. The correct recognition rate for synthetic data for Eigenfaces is 99% based on Euclidean Distance. The overall accuracy of Eigenfaces is 97% based on 6144 degraded samples and considering Euclidean Distance performance criterion. Conclusions: It is concluded from the experimental results that the Eigenfaces method is suitable for font recognition of degraded documents. The three percentage incorrect classification can be mediated by relying on intra-word font information.