A New Offline Persian Hand Writer Recognition based on 2D-Wavelet Transforms
Автор: Keivan Borna, Vahid Hajihashemi
Журнал: International Journal of Image, Graphics and Signal Processing(IJIGSP) @ijigsp
Статья в выпуске: 9 vol.7, 2015 года.
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All the works on writer's handwritten letters detection was based on the western languages and partly Chinese and Hindi, and there is a little study on Persian handwritten letters detection. Accordingly, in this paper a method is proposed to distinguish scanned Persian handwritten texts with image processing techniques. The proposed method assumes that the writer's handwritten are available in separate letters. The system trains with features extraction of these separate letters and then the trained system is used to detect individual handwritten among some indistinctive handwritten texts. The characteristics of our proposed method including high-speed of training in too much number of handwritten, is the content inattention and visual features considering. The results of procedures on 100 persons also admitted that the proposed method has a very good performance on Persian handwritten texts detection.
Writers' handwritten identification, handwritten, wavelet transform, nearest neighbor search
Короткий адрес: https://sciup.org/15013905
IDR: 15013905
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