Development of algorithms for face and character recognition based on wavelet transforms, PCA and neural networks

T. T T Bui, N. H. Phan, V. G. Spitsyn, Yu A. Bolotova, Yu V. Savitsky

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции

2 Цитирования (Scopus)

Аннотация

In this paper we present a novel algorithms for face and character recognition using combination of wavelet transforms and principal component analysis (PCA). At first, face features are extracted using combination of Haar and Daubechies wavelet transform. Then obtained features are used for face recognition by PCA (eigenfaces). In the case of character recognition we use combination of wavelet transform and principal component analysis for character feature extraction. Then obtained extracted features are classified using multi-layer feed-forward neural networks. For each training character we use one neural network, which determines the confidence whether an input character is its prototype or not. The proposed algorithms give an effective performance of face and character recognition on noisy images and compete with state-of-the-art algorithms.

Язык оригиналаАнглийский
Название основной публикации2015 International Siberian Conference on Control and Communications, SIBCON 2015 - Proceedings
ИздательInstitute of Electrical and Electronics Engineers Inc.
ISBN (печатное издание)9781479971022
DOI
СостояниеОпубликовано - 1 июл 2015
Событие2015 International Siberian Conference on Control and Communications, SIBCON 2015 - Omsk, Российская Федерация
Продолжительность: 21 мая 201523 мая 2015

Другое

Другое2015 International Siberian Conference on Control and Communications, SIBCON 2015
СтранаРоссийская Федерация
ГородOmsk
Период21.5.1523.5.15

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Systems Engineering

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