کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
530549 | 869774 | 2013 | 8 صفحه PDF | دانلود رایگان |

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.
Journal: Pattern Recognition - Volume 46, Issue 7, July 2013, Pages 1898–1905