Thongkanchorn et al., 2019 - Google Patents
Thai character segmentation in handwriting images using four directional depth first searchThongkanchorn et al., 2019
- Document ID
- 7169549286648436142
- Author
- Thongkanchorn K
- Kanchanapreechakorn S
- Borwarnginn P
- Kusakunniran W
- Publication year
- Publication venue
- 2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)
External Links
Snippet
One of the key processes for converting handwriting images into digital texts is the character segmentation. It is very challenge especially for the case of segmenting the hand-writing due to intra-variations of various writing styles and overlapping of characters between …
- 230000011218 segmentation 0 title abstract description 20
Classifications
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- G06K9/20—Image acquisition
- G06K9/34—Segmentation of touching or overlapping patterns in the image field
- G06K9/342—Cutting or merging image elements, e.g. region growing, watershed, clustering-based techniques
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
- G06K9/6807—Dividing the references in groups prior to recognition, the recognition taking place in steps; Selecting relevant dictionaries
- G06K9/6814—Dividing the references in groups prior to recognition, the recognition taking place in steps; Selecting relevant dictionaries according to the graphical properties
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- G06K9/34—Segmentation of touching or overlapping patterns in the image field
- G06K9/348—Segmentation of touching or overlapping patterns in the image field using character size, text spacings, pitch estimation
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- G06K9/2072—Selective acquisition/locating/processing of specific regions, e.g. highlighted text, fiducial marks, predetermined fields, document type identification based on positionally close symbols, e.g. amount sign or URL-specific characters
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