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Deskewing Algorithm for Unconstrained Handwritten Kannada Documents Leading to Line and Word Segmentation
| Content Provider | Semantic Scholar |
|---|---|
| Author | Angadi, Shanmukhappa A. Angadi, Sharanabasavaraj. H. |
| Copyright Year | 2016 |
| Abstract | 34 Abstract— Extraction of lines and words from handwritten document images containing skewed text is one of th e most difficult and challenging problem. In this paper, a new deskewing algorithm leading to line and word segmen tation from an unconstrained hand written Kannada document s is proposed. The method employs preprocessing, dilation and labelling the connected components of input image a s initial step. Then an intelligent technique is used to grou p the words belonging to a text line. The extracted words are s ubjected to removal of unwanted information that pertains to adjacent words. Further the skew angle computation and rotat ion operation (when angle is other than zero) are perfo rmed for purpose of deskewing of extracted words. Then deskewd words are intelligently written into new image without overlapping of words in text line. The method also takes care of de tecting text lines containing consonant modifiers. Inter word and intra character gap variations are also taken care at the time of word segmentation by the proposed method. The method is e valuated for 20 images having 166 lines and 823 words. A lin e segmentation accuracy of 96.38% and word segmentati on accuracy of 92.10% is achieved. The method works eff iciently for document images containing skew upto four degre es. The method also works correctly even in the presence co nsonant and vowel modifiers, compound characters and uneven spa cing between characters and words. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijetcse.com/wp-content/plugins/ijetcse/file/upload/docx/227DESKEWING-ALGORITHM-FOR-UNCONSTRAINED-HANDWRITTEN-KANNADA-DOCUMENTS-LEADING-TO-LINE-AND-WORD-SEGMENTATION-pdf.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
