Classification of handwritten characters by their symmetry features

Sam Holland; Richard Neville

doi:10.1109/ACT.2009.85

Classification of handwritten characters by their symmetry features

Sam Holland, Richard Neville

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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Abstract

We propose a technique to classify characters by two different forms of their symmetry features. The Generalized Symmetry Transform is applied to digits from the USPS data set. These features are then used to train Probabilistic Neural Networks and their performances are compared to the traditional method. © 2009 IEEE.

Original language	English
Title of host publication	ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies\|ACT - Int. Conf. Adv. Comput., Control Telecommun. Technol.
Publisher	IEEE
Pages	316-318
Number of pages	2
ISBN (Print)	9780769539157
DOIs	https://doi.org/10.1109/ACT.2009.85
Publication status	Published - 2009
Event	International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2009 - Trivandrum, Kerala Duration: 1 Jul 2009 → …

Conference

Conference	International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2009
City	Trivandrum, Kerala
Period	1/07/09 → …

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10.1109/ACT.2009.85

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@inproceedings{17d836506b1341bfa30d86964e78f62a,

title = "Classification of handwritten characters by their symmetry features",

abstract = "We propose a technique to classify characters by two different forms of their symmetry features. The Generalized Symmetry Transform is applied to digits from the USPS data set. These features are then used to train Probabilistic Neural Networks and their performances are compared to the traditional method. {\textcopyright} 2009 IEEE.",

author = "Sam Holland and Richard Neville",

year = "2009",

doi = "10.1109/ACT.2009.85",

language = "English",

isbn = "9780769539157",

pages = "316--318",

booktitle = "ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies|ACT - Int. Conf. Adv. Comput., Control Telecommun. Technol.",

publisher = "IEEE",

address = "United States",

note = "International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2009 ; Conference date: 01-07-2009",

}

Holland, S & Neville, R 2009, Classification of handwritten characters by their symmetry features. in ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies|ACT - Int. Conf. Adv. Comput., Control Telecommun. Technol.. IEEE, pp. 316-318, International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2009, Trivandrum, Kerala, 1/07/09. https://doi.org/10.1109/ACT.2009.85

Classification of handwritten characters by their symmetry features. / Holland, Sam; Neville, Richard.
ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies|ACT - Int. Conf. Adv. Comput., Control Telecommun. Technol.. IEEE, 2009. p. 316-318.

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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T1 - Classification of handwritten characters by their symmetry features

AU - Holland, Sam

AU - Neville, Richard

PY - 2009

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AB - We propose a technique to classify characters by two different forms of their symmetry features. The Generalized Symmetry Transform is applied to digits from the USPS data set. These features are then used to train Probabilistic Neural Networks and their performances are compared to the traditional method. © 2009 IEEE.

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DO - 10.1109/ACT.2009.85

M3 - Conference contribution

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SP - 316

EP - 318

BT - ACT 2009 - International Conference on Advances in Computing, Control and Telecommunication Technologies|ACT - Int. Conf. Adv. Comput., Control Telecommun. Technol.

PB - IEEE

T2 - International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2009

Y2 - 1 July 2009

ER -

Classification of handwritten characters by their symmetry features

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