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Erschienen in:

2018 | OriginalPaper | Buchkapitel

Research on the Methods for Extracting the Sensitive Uyghur Text-Images for Digital Forensics

verfasst von : Yasen Aizezi, Anniwaer Jiamali, Ruxianguli Abdurixiti, Kurban Ubul

Erschienen in: Biometric Recognition

Verlag: Springer International Publishing

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Abstract

With the continuous development of filtration technology for text information, many criminal offenders made much harmful text information in Uyghur involving extreme religion and terrorism information by image editing software. In order to recognize the Uyghur text-images effectively, a scheme for recognizing printed Uyghur based on the features extracted by histogram of oriented gradient (HOG) and the multilayer perceptron (MLP) neural network is put forward. Firstly, preprocess the Uyghur text-images to obtain the binary images after eliminating noise. After that, segment the text-line by horizontal projection integral method and segment the words and characters by vertical projection integral method to obtain independent characters. Next, extract the features of characters by HOG. Finally, recognize the characters through the trained MLP neural network classifier and according to features extract by HOG. The experimental results showed that we could recognize Uyghur characters accurately by the method put forward.

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Vorheriges Kapitel BoVW Based Feature Selection for Uyghur Offline Signature Verification

Nächstes Kapitel A Study on the Printed Uyghur Script Recognition Technique Using Word Visual Features

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Titel: Research on the Methods for Extracting the Sensitive Uyghur Text-Images for Digital Forensics
verfasst von: Yasen Aizezi
Anniwaer Jiamali
Ruxianguli Abdurixiti
Kurban Ubul
Verlag: Springer International Publishing
Buch: Biometric Recognition
Print ISBN: 978-3-319-97908-3

Electronic ISBN: 978-3-319-97909-0

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-97909-0_75

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