Word recognition in a segmentation-free approach to OCR

Prasanna G. Mulgaonkar; Chien-Huei Chen; Jeff L. DeCurtins

doi:10.1117/12.169464

25 February 1994 Word recognition in a segmentation-free approach to OCR

Prasanna G. Mulgaonkar, Chien-Huei Chen, Jeff L. DeCurtins

Proceedings Volume 2103, 22nd AIPR Workshop: Interdisciplinary Computer Vision: Applications and Changing Needs; (1994) https://doi.org/10.1117/12.169464
Event: 22nd Applied Imagery Pattern Recognition Workshop, 1993, Washington, DC, United States

Abstract

Segmentation is a key step in current OCR systems. It has been estimated that half the errors in character recognition are due to segmentation. We have developed a novel approach that performs OCR without the segmentation step. The approach starts by extracting significant geometric features from the input document image of the page. Each feature then `votes' for the character that could have generated that feature. Thus, even if some of the features are occluded or lost due to degradation, the remaining features can successfully identify the character. In extreme case, the degradation may be severe enough to prevent recognition of some of the characters in a word. In such cases, we use a lexicon-based word recognition technique to resolve ambiguity. Inexact matching and probabilistic evaluation used in the technique allow us to identify the correct word, by detecting a partial set of characters. This paper first presents an overview of our segmentation-free OCR system and then focuses on the word-recognition technique. Preliminary experimental results show that this is a very promising approach.

Citation Download Citation

Prasanna G. Mulgaonkar, Chien-Huei Chen, and Jeff L. DeCurtins "Word recognition in a segmentation-free approach to OCR", Proc. SPIE 2103, 22nd AIPR Workshop: Interdisciplinary Computer Vision: Applications and Changing Needs, (25 February 1994); https://doi.org/10.1117/12.169464

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