Segmentation of Broken Khmer Characters
| dc.contributor.author | Pravesjit S. | |
| dc.contributor.author | Kantawong K. | |
| dc.contributor.author | That V. | |
| dc.contributor.author | Longpradit P. | |
| dc.contributor.other | Mahidol University | |
| dc.date.accessioned | 2023-06-18T17:03:05Z | |
| dc.date.available | 2023-06-18T17:03:05Z | |
| dc.date.issued | 2022-01-01 | |
| dc.description.abstract | Preprocessing is the first step in handwritten characters recognition. Segmentation is an important preprocessing step for separate group of words into single character. Broken character is one of the most difficult segmentation cases which arise when handwritten characters are being segmented. Therefore, this paper focuses on the segmentation of broken characters. The proposed character segmentation workflow consists of finding the middle layer of words by the projection analysis and bounding box analysis which is initially employed to segment the document image into images of isolated characters and images of broken characters. The thinning algorithm is then applied to extract the skeleton of the characters in middle layer and file loop, junction point, vertex shape and straight line by chain code algorithm. Finally, the rules for combining characters from the aspect ratio value (height/width), together with the separated pieces of the broken Khmer characters, are put back to reconstruct one isolated characters. The proposed algorithm achieves an accuracy of 79.5%. | |
| dc.identifier.citation | 2022 3rd International Conference on Big Data Analytics and Practices, IBDAP 2022 (2022) , 65-68 | |
| dc.identifier.doi | 10.1109/IBDAP55587.2022.9907272 | |
| dc.identifier.scopus | 2-s2.0-85141579275 | |
| dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/123456789/84350 | |
| dc.rights.holder | SCOPUS | |
| dc.subject | Computer Science | |
| dc.title | Segmentation of Broken Khmer Characters | |
| dc.type | Conference Paper | |
| mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85141579275&origin=inward | |
| oaire.citation.endPage | 68 | |
| oaire.citation.startPage | 65 | |
| oaire.citation.title | 2022 3rd International Conference on Big Data Analytics and Practices, IBDAP 2022 | |
| oairecerif.author.affiliation | University of Phayao | |
| oairecerif.author.affiliation | Mahidol University |
