Performance improvements to the BBN Byblos OCR system
Michael Decerbo, Prem Natarajan, Rohit Prasad, Ehry MacRostie, Arun Ravindran · 2005
In this paper, we describe four recent enhancements to the BBN Byblos OCR system, a multilingual HMM-based character recognition system which has been demonstrated on a variety of languages, including English, Arabic, Chinese, and Japanese. These enhancements are implemented as optional extensions to the system and provide improved performance for certain scripts or domains. Projection-based re-estimation of line boundaries reduces instability in the presence of some types of noise. An alternate modeling strategy used in the first of two recognition search passes substantially increases speed on languages with a large number of characters. Another speed improvement comes from automatic discovery and modeling of sub-characters. The use of heteroschedastic linear discriminant analysis (HLDA) makes modeling more tractable by reducing feature-space dimensionality.