Boost OCR accuracy using iVector based system combination approach
2015
Optical character recognition (OCR) is a challenging task because most existing preprocessing approaches are
sensitive to writing style, writing material, noises and image resolution. Thus, a single recognition system cannot
address all factors of real document images. In this paper, we describe an approach to combine diverse recognition
systems by using iVector based features, which is a newly developed method in the field of speaker verification.
Prior to system combination, document images are preprocessed and text line images are extracted with different
approaches for each system, where iVector is transformed from a high-dimensional supervector of each text line
and is used to predict the accuracy of OCR. We merge hypotheses from multiple recognition systems according
to the overlap ratio and the predicted OCR score of text line images. We present evaluation results on an Arabic
document database where the proposed method is compared against the single best OCR system using word
error rate (WER) metric.
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