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Word Spotting as a Service: An Unsupervised and Segmentation-Free Framework for Handwritten Documents
by
Amanatiadis, Angelos
, Zagoris, Konstantinos
, Pratikakis, Ioannis
in
Cloud computing
/ cloud service
/ document-oriented features
/ Documents
/ Electronic devices
/ Feature extraction
/ Handwriting
/ handwritten documents
/ Image retrieval
/ indexing
/ Matching
/ Queries
/ Segmentation
/ word spotting
2021
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Word Spotting as a Service: An Unsupervised and Segmentation-Free Framework for Handwritten Documents
by
Amanatiadis, Angelos
, Zagoris, Konstantinos
, Pratikakis, Ioannis
in
Cloud computing
/ cloud service
/ document-oriented features
/ Documents
/ Electronic devices
/ Feature extraction
/ Handwriting
/ handwritten documents
/ Image retrieval
/ indexing
/ Matching
/ Queries
/ Segmentation
/ word spotting
2021
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Do you wish to request the book?
Word Spotting as a Service: An Unsupervised and Segmentation-Free Framework for Handwritten Documents
by
Amanatiadis, Angelos
, Zagoris, Konstantinos
, Pratikakis, Ioannis
in
Cloud computing
/ cloud service
/ document-oriented features
/ Documents
/ Electronic devices
/ Feature extraction
/ Handwriting
/ handwritten documents
/ Image retrieval
/ indexing
/ Matching
/ Queries
/ Segmentation
/ word spotting
2021
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Word Spotting as a Service: An Unsupervised and Segmentation-Free Framework for Handwritten Documents
Journal Article
Word Spotting as a Service: An Unsupervised and Segmentation-Free Framework for Handwritten Documents
2021
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Overview
Word spotting strategies employed in historical handwritten documents face many challenges due to variation in the writing style and intense degradation. In this paper, a new method that permits efficient and effective word spotting in handwritten documents is presented that relies upon document-oriented local features that take into account information around representative keypoints and a matching process that incorporates a spatial context in a local proximity search without using any training data. The method relies on a document-oriented keypoint and feature extraction, along with a fast feature matching method. This enables the corresponding methodological pipeline to be both effectively and efficiently employed in the cloud so that word spotting can be realised as a service in modern mobile devices. The effectiveness and efficiency of the proposed method in terms of its matching accuracy, along with its fast retrieval time, respectively, are shown after a consistent evaluation of several historical handwritten datasets.
Publisher
MDPI AG,MDPI
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