Feature Extraction Comparison in Handwriting Recognition of Batak Toba Alphabet
2018 ◽
Vol 1
(3)
◽
pp. 86
Keyword(s):
Offline handwriting recognition is one of the most prominent research topics due to its tremendous application and high variability as well. This paper covers the offline Batak Toba handwritten text recognition, from the noise removal, the process of feature extraction until the recognition by using several classifiers. Experiments show that elliptic fourier descriptor (EFD) is the most discriminative feature and Mahalanobis distance (MD) outperforms the two others classifier.
2019 ◽
Vol 10
(4)
◽
pp. 26-45
◽
2019 ◽
Vol 9
(2)
◽
pp. 1394-1397
2020 ◽
Vol 14
(01)
◽
pp. 161
2021 ◽
Vol 10
(3)
◽
pp. 1627-1631
Keyword(s):
Keyword(s):
2021 ◽
Vol 5
(1)
◽
pp. 21
Keyword(s):