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Context-directed segmentation algorithm for handwritten numeral strings

dc.contributor.authorShridhar, M.en_US
dc.contributor.authorBadreldin, A.en_US
dc.date.accessioned2006-04-07T19:57:12Z
dc.date.available2006-04-07T19:57:12Z
dc.date.issued1987-02en_US
dc.identifier.citationShridhar, M, Badreldin, A (1987/02)."Context-directed segmentation algorithm for handwritten numeral strings." Image and Vision Computing 5(1): 3-9. <http://hdl.handle.net/2027.42/26810>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6V09-48TD9CK-6D/2/74bc2eb9bbf428968cd5bc2db5b16355en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/26810
dc.description.abstractA context-directed algorithm is proposed for segmenting connected numeral strings into their components. The algorithm is hierarchical (tree-like structure) in the sense that it tests various hypotheses ranging from the case where the numerals are completely isolated to that where the numerals may be connected, touching and/or existing in overlapping fields. Test results indicate that the algorithm is very effective in providing an accurate segmentation in a form suitable for further processing by a recognition algorithm.en_US
dc.format.extent1771472 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleContext-directed segmentation algorithm for handwritten numeral stringsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelComputer Scienceen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI 48128-1491, USAen_US
dc.contributor.affiliationotherInstrumentation Department, General Motors Research Laboratories, Warren, MI 48090-9055, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/26810/1/0000366.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0262-8856(87)90071-0en_US
dc.identifier.sourceImage and Vision Computingen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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