| Autor: |
Konstantinos Zagoris, Angelos Amanatiadis, Ioannis Pratikakis |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Journal of Imaging, Vol 7, Iss 12, p 278 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2313-433X |
| DOI: |
10.3390/jimaging7120278 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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