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- W2069477413 abstract "Recognition of alphabetic characters is a basic need in incorporating intelligence to computers. Machine intelligence involves several aspects among which optical recognition is a tool, which can be integrated to text recognition. To make these aspects effective character recognition with better accuracy is important. However, handwritten character recognition is still a difficult task because of the high variability in the character shapes written by individuals. While large amount of work has been done towards recognition of handwritten English characters relatively less work is reported for the recognition of Indian language scripts. So, we proposed a new elastic image matching (EM) technique based on an eigen-deformation for recognition of offline isolated English uppercase handwritten characters and offline isolated handwritten characters of Devnagari, the most popular script in India. Deformations in handwritten characters have category-dependent tendencies. The estimation and the utilization of such tendencies called eigen-deformations are investigated for the better performance of elastic matching based handwritten character recognition. The eigen-deformations are estimated by the principal component analysis of actual deformations automatically collected by the elastic matching. Typical deformations of each category can be extracted as the eigen-deformations. According to a similarity measure (e.g.: Euclidean, Mahalanobis similarity measures etc.), a prototype matching is done for recognition." @default.
- W2069477413 created "2016-06-24" @default.
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- W2069477413 date "2009-01-23" @default.
- W2069477413 modified "2023-09-23" @default.
- W2069477413 title "Handwritten character recognition using elastic matching and PCA" @default.
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- W2069477413 doi "https://doi.org/10.1145/1523103.1523184" @default.
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