Feature space denoising improves word spotting
2013 (English)In: Proc. 2nd International Workshop on Historical Document Imaging and Processing, New York: ACM Press, 2013, 59-66 p.Conference paper (Refereed)
Some of the sliding window features commonly used in off-line handwritten text recognition are inherently noisy or sen-sitive to image noise. In this paper, we investigate the ef-fects of several de-noising filters applied in the feature spaceand not in the image domain. The purpose is to target theintrinsic noise of these features, stemming from the com-plex shapes of handwritten characters. This noise is presenteven if the image has been captured without any kind ofartefacts or noise. An evaluation, using a public database,is presented showing that the recognition of word-spottingcan be improved considerably by using de-noising filters inthe feature space.
Place, publisher, year, edition, pages
New York: ACM Press, 2013. 59-66 p.
OCR, handwritten text recognition, filtering
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:uu:diva-206930DOI: 10.1145/2501115.2501118ISBN: 978-1-4503-2115-0OAI: oai:DiVA.org:uu-206930DiVA: diva2:646245
2nd International Workshop on Historical Document Imaging and Processing