Segmentation-free keyword spotting framework using dynamic background model

Gaurav Kumar; Safwan Wshah; Venu Govindaraju; Sitaram Ramachandrula

doi:10.1117/12.2008597

4 February 2013 Segmentation-free keyword spotting framework using dynamic background model

Gaurav Kumar, Safwan Wshah, Venu Govindaraju, Sitaram Ramachandrula

Proceedings Volume 8658, Document Recognition and Retrieval XX; 86580H (2013) https://doi.org/10.1117/12.2008597
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

We propose a segmentation free word spotting framework using Dynamic Background Model. The proposed approach is an extension to our previous work where dynamic background model was introduced and integrated with a segmentation based recognizer for keyword spotting. The dynamic background model uses the local character matching scores and global word level hypotheses scores to separate keywords from non-keywords. We integrate and evaluate this model on Hidden Markov Model (HMM) based segmentation free recognizer which works at line level without any need for word segmentation. We outperform the state of the art line level word spotting system on IAM dataset.

Citation Download Citation

Gaurav Kumar, Safwan Wshah, Venu Govindaraju, and Sitaram Ramachandrula "Segmentation-free keyword spotting framework using dynamic background model", Proc. SPIE 8658, Document Recognition and Retrieval XX, 86580H (4 February 2013); https://doi.org/10.1117/12.2008597

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