کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6938778 | 1449965 | 2018 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Two combination stages of clustered One-Class Classifiers for writer identification from text fragments
ترجمه فارسی عنوان
دو مرحله ترکیبی طبقه بندی طبقه بندی شده خوشه ای برای شناسایی نویسنده از قطعات متن
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Writer identification based on handwritten fragments has been reported to give interesting performance. However, while the fragmentation process, inconsistent fragments are generated and affect badly the identification accuracy. Hence, in this paper, a clustered-based One-Class Classifier (OCC) is proposed in order to generate more robust classification model than the distance-based classifier for handwritten fragments. Besides, the problem of inconsistent fragments expands its effect to the test step. Thus, a Dynamic Fragment Weighting Combination (DFWC) rule is proposed to reduce the effect of inconsistent test fragments. Furthermore, due to the difficulty of performing a generic descriptor, three different descriptors related systems are designed and combined through an effective combination scheme based on Choquet fuzzy integral operator. Experimental results conducted on the well-known IFN/ENIT and IAM datasets show good adaptation of the OCC with DFWC. Moreover, the Choquet combination scheme offers more improvements to achieve 97.56% and 94.51% for the used datasets, respectively. The obtained results highlight the reliability of the proposed system in comparison with recent studies for writer identification issue.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 82, October 2018, Pages 147-162
Journal: Pattern Recognition - Volume 82, October 2018, Pages 147-162
نویسندگان
Bilal Hadjadji, Youcef Chibani,