کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
530549 869774 2013 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Large-scale document image retrieval and classification with runlength histograms and binary embeddings
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Large-scale document image retrieval and classification with runlength histograms and binary embeddings
چکیده انگلیسی

We present a new document image descriptor based on multi-scale runlength histograms. This descriptor does not rely on layout analysis and can be computed efficiently. We show how this descriptor can achieve state-of-the-art results on two very different public datasets in classification and retrieval tasks. Moreover, we show how we can compress and binarize these descriptors to make them suitable for large-scale applications. We can achieve state-of-the-art results in classification using binary descriptors of as few as 16–64 bits.


► We present a document image descriptor based on multi-scale runlength histograms.
► This descriptor does not need layout analysis and can be computed efficiently.
► We compress and binarize the descriptors to make them suitable for large-scale.
► State-of-the-art results on two public datasets.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 46, Issue 7, July 2013, Pages 1898–1905
نویسندگان
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