Multi-layer perceptron network for English character recognition

Musa Ibrahim Bello, Iliyasu Adamu, Hilary Watsilla, Kabir Ismail Umar

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The recognition of English language character is an interesting area in recognition of pattern. Within this article, effort has been made to design a program that will recognize English characters with a multilayer perceptron having only a single hidden layer. Fourier descriptors and boundary trace are features extracted off the English characters. The shape of each character is analyzed and used to identify and compare its features that differentiates each character. Determining numerals of hidden layer neurons was analyzed in other to attain great back propagation performance in English language character recognition. Training of the network was done with 78 samples collection of English characters and was tested on 78 samples different from the training samples which indicated that Fourier description together with back propagation provides decent accuracy of recognition at 95% for characters having a smaller amount of classification and training period.
Original languageEnglish
Pages (from-to)86-92
Number of pages7
JournalAmerican Journal of Engineering Research (AJER)
Issue number6
Publication statusPublished - 31 Dec 2017


  • multi-layer perceptron network
  • English character recognition


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