Feature extraction from printed Persian sub-words using Haar wavelet transform

被引:0
作者
Dizajyekan, Samira Nasrollahi [1 ]
Ebrahimi, Afshin [1 ]
机构
[1] Sahand Univ Technol, Dept Elect Engn, Tabriz, Iran
来源
THIRD INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2011) | 2011年 / 8009卷
关键词
Shape descriptor; Sub-words; Haar wavelet transform; Feature extraction; Post-processing; RECOGNITION;
D O I
10.1117/12.896300
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
This article presents a novel set of shape descriptors which are especially well-suited for the recognition of printed Persian sub-words based on their holistic shapes. The descriptor set is derived from the wavelet transform of a sub-word's image. The proposed algorithm is used to extract features from 87804 sub-words of 4 fonts and 3 sizes. To evaluate the feature extraction results, this algorithm was used to obtain recognition rate for a set of sub-words in a printed Persian text document. Features of an unknown sub-word are extracted and compared with all sub-words features in the dictionary and the desired sub-word is identified. In this stage to increase the recognition rate, dot features of the unknown sub-word are used as the second feature and compared with dot codes of 10 last sub-words in before stage and the sub-word with maximum similarity is extracted as correct recognized sub-word.
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页数:5
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