Texture Features based Blur Classification in Barcode Images

Texture Features based Blur Classification in Barcode Images

Автор: Shamik Tiwari, Vidya Prasad Shukla, Sangappa Biradar, Ajay Singh

Журнал: International Journal of Information Engineering and Electronic Business(IJIEEB) @ijieeb

Статья в выпуске: 5 vol.5, 2013 года.

Бесплатный доступ

Blur is an undesirable phenomenon which appears as image degradation. Blur classification is extremely desirable before application of any blur parameters estimation approach in case of blind restoration of barcode image. A novel approach to classify blur in motion, defocus, and co-existence of both blur categories is presented in this paper. The key idea involves statistical features extraction of blur pattern in frequency domain and designing of blur classification system with feed forward neural network.

Blur, Motion, Defocus, Texture feature, Neural Network, Pattern Classification

Короткий адрес: https://sciup.org/15013210

IDR: 15013210

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