Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDAR.2007.4377062
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dc.titleRemoving shading distortions in camera-based document images using inpainting and surface fitting with radial basis functions
dc.contributor.authorZhang, L.
dc.contributor.authorYip, A.M.
dc.contributor.authorChew, L.T.
dc.date.accessioned2013-07-23T09:31:29Z
dc.date.available2013-07-23T09:31:29Z
dc.date.issued2007
dc.identifier.citationZhang, L.,Yip, A.M.,Chew, L.T. (2007). Removing shading distortions in camera-based document images using inpainting and surface fitting with radial basis functions. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR 2 : 984-988. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ICDAR.2007.4377062" target="_blank">https://doi.org/10.1109/ICDAR.2007.4377062</a>
dc.identifier.isbn0769528228
dc.identifier.issn15205363
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/43343
dc.description.abstractShading distortions are often perceived in geometrically distorted document images due to the change of surface normal with respect to the illumination direction. Such distortions are undesirable because they hamper OCR performance tremendously even when the geometric distortions are corrected. In this paper, we propose an effective method that removes shading distortions in images of documents with various geometric shapes based on the notion of intrinsic images. We first try to derive the shading image using an inpainting technique with an automatic mask generation routine and then apply a surface fitting procedure with radial basis functions to remove pepper noises in the inpainted image and return a smooth shading image. Once the shading image is extracted, the reflectance image can be obtained automatically. Experiments on a wide range of distorted document images demonstrate a robust performance. Moreover, we also show its potential applications to the restoration of historical handwritten documents.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICDAR.2007.4377062
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.contributor.departmentMATHEMATICS
dc.description.doi10.1109/ICDAR.2007.4377062
dc.description.sourcetitleProceedings of the International Conference on Document Analysis and Recognition, ICDAR
dc.description.volume2
dc.description.page984-988
dc.identifier.isiutNOT_IN_WOS
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