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Performance evaluation methodology for historical document image binarization
Document image binarization is of great importance in the document image analysis and
recognition pipeline since it affects further stages of the recognition process. The evaluation …
recognition pipeline since it affects further stages of the recognition process. The evaluation …
[PDF][PDF] An optimal machine learning model based on selective reinforced Markov decision to predict web browsing patterns
The abundance of user usage data has gained exponential dimensions as a result of the
ongoing expansion and spread of Web applications and Web-based systems. Web user …
ongoing expansion and spread of Web applications and Web-based systems. Web user …
Unsupervised segmentation of fire and smoke from infra-red videos
This paper proposes a vision-based fire and smoke segmentation system which uses
spatial, temporal and motion information to extract the desired regions from the video …
spatial, temporal and motion information to extract the desired regions from the video …
A local linear level set method for the binarization of degraded historical document images
Document image binarization is a difficult task, especially for complex document images.
Nonuniform background, stains, and variation in the intensity of the printed characters are …
Nonuniform background, stains, and variation in the intensity of the printed characters are …
An improved scene text extraction method using conditional random field and optical character recognition
H Zhang, C Liu, C Yang, X Ding… - … on Document Analysis …, 2011 - ieeexplore.ieee.org
Over the past few years, research on scene text extraction has developed rapidly. Recently,
condition random field (CRF) has been used to give connected components …
condition random field (CRF) has been used to give connected components …
Handwritten text separation from annotated machine printed documents using Markov Random Fields
The convenience of search, both on the personal computer hard disk as well as on the web,
is still limited mainly to machine printed text documents and images because of the poor …
is still limited mainly to machine printed text documents and images because of the poor …
Text segmentation for MRC document compression
The mixed raster content (MRC) standard (ITU-T T. 44) specifies a framework for document
compression which can dramatically improve the compression/quality tradeoff as compared …
compression which can dramatically improve the compression/quality tradeoff as compared …
Hyperspectral image classification using spatial and edge features based on deep learning
D Zhang, J Kang, L Xun, Y Huang - International Journal of Pattern …, 2019 - World Scientific
In recent years, deep learning has been widely used in the classification of hyperspectral
images and good results have been achieved. But it is easy to ignore the edge information …
images and good results have been achieved. But it is easy to ignore the edge information …
Model-based ruling line detection in noisy handwritten documents
Ruling lines are commonly used to help people write neatly on paper. In document analysis,
however, they raise hurdles for the tasks of handwriting recognition or writer identification. In …
however, they raise hurdles for the tasks of handwriting recognition or writer identification. In …
Neural networks for document image and text processing
J Pastor Pellicer - 2017 - riunet.upv.es
Avui en dia, les principals llibreries i arxius històrics estan invertint un esforç considerable
en la digitalització de les seues col· leccions de documents. De fet, la majoria estan …
en la digitalització de les seues col· leccions de documents. De fet, la majoria estan …