کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4969819 1449984 2017 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Writer Identification Using GMM Supervectors and Exemplar-SVMs
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Writer Identification Using GMM Supervectors and Exemplar-SVMs
چکیده انگلیسی
This paper describes a method for robust offline writer identification. We propose to use RootSIFT descriptors computed densely at the script contours. GMM supervectors are used as encoding method to describe the characteristic handwriting of an individual scribe. GMM supervectors are created by adapting a background model to the distribution of local feature descriptors. Finally, we propose to use Exemplar-SVMs to train a document-specific similarity measure. We evaluate the method on three publicly available datasets (ICDAR / CVL / KHATT) and show that our method sets new performance standards on all three datasets. Additionally, we compare different feature sampling strategies as well as other encoding methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 63, March 2017, Pages 258-267
نویسندگان
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