FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2048049573> ?p ?o ?g. }

• W2048049573 endingPage "4136" @default.
• W2048049573 startingPage "4124" @default.
• W2048049573 abstract "There are printed complex documents where text lines of a single page may have different orientations or the text lines may be curved in shape. As a result, it is difficult to detect the skew of such documents and hence character segmentation and recognition of such documents are a complex task. In this paper, using background and foreground information we propose a novel scheme towards the recognition of Indian complex documents of Bangla and Devnagari script. In Bangla and Devnagari documents usually characters in a word touch and they form cavity regions. To take care of these cavity regions, background information of such documents is used. Convex hull and water reservoir principle have been applied for this purpose. Here, at first, the characters are segmented from the documents using the background information of the text. Next, individual characters are recognized using rotation invariant features obtained from the foreground part of the characters. For character segmentation, at first, writing mode of a touching component (word) is detected using water reservoir principle based features. Next, depending on writing mode and the reservoir base-region of the touching component, a set of candidate envelope points is then selected from the contour points of the component. Based on these candidate points, the touching component is finally segmented into individual characters. For recognition of multi-sized/multi-oriented characters the features are computed from different angular information obtained from the external and internal contour pixels of the characters. These angular information are computed in such a way that they do not depend on the size and rotation of the characters. Circular and convex hull rings have been used to divide a character into smaller zones to get zone-wise features for higher recognition results. We combine circular and convex hull features to improve the results and these features are fed to support vector machines (SVM) for recognition. From our experiment we obtained recognition results of 99.18% (98.86%) accuracy when tested on 7515 (7874) Devnagari (Bangla) characters." @default.
• W2048049573 created "2016-06-24" @default.
• W2048049573 creator A5036208317 @default.
• W2048049573 creator A5065907624 @default.
• W2048049573 creator A5068803496 @default.
• W2048049573 creator A5090517096 @default.
• W2048049573 date "2010-12-01" @default.
• W2048049573 modified "2023-09-29" @default.
• W2048049573 title "Multi-oriented Bangla and Devnagari text recognition" @default.
• W2048049573 cites W1509564083 @default.
• W2048049573 cites W1548607474 @default.
• W2048049573 cites W1968677253 @default.
• W2048049573 cites W1975512060 @default.
• W2048049573 cites W1983275987 @default.
• W2048049573 cites W1986216697 @default.
• W2048049573 cites W1996110654 @default.
• W2048049573 cites W2001895919 @default.
• W2048049573 cites W2005182288 @default.
• W2048049573 cites W2029189646 @default.
• W2048049573 cites W2035575611 @default.
• W2048049573 cites W2053123339 @default.
• W2048049573 cites W2054797853 @default.
• W2048049573 cites W2082183672 @default.
• W2048049573 cites W2085638554 @default.
• W2048049573 cites W2096047360 @default.
• W2048049573 cites W2099790389 @default.
• W2048049573 cites W2107135714 @default.
• W2048049573 cites W2107918262 @default.
• W2048049573 cites W2118376687 @default.
• W2048049573 cites W2126738248 @default.
• W2048049573 cites W2141707484 @default.
• W2048049573 cites W2145219790 @default.
• W2048049573 cites W2155818555 @default.
• W2048049573 cites W2158472161 @default.
• W2048049573 cites W2163644233 @default.
• W2048049573 cites W2165437683 @default.
• W2048049573 cites W2322794882 @default.
• W2048049573 doi "https://doi.org/10.1016/j.patcog.2010.06.017" @default.
• W2048049573 hasPublicationYear "2010" @default.
• W2048049573 type Work @default.
• W2048049573 sameAs 2048049573 @default.
• W2048049573 citedByCount "47" @default.
• W2048049573 countsByYear W20480495732012 @default.
• W2048049573 countsByYear W20480495732013 @default.
• W2048049573 countsByYear W20480495732014 @default.
• W2048049573 countsByYear W20480495732015 @default.
• W2048049573 countsByYear W20480495732016 @default.
• W2048049573 countsByYear W20480495732017 @default.
• W2048049573 countsByYear W20480495732018 @default.
• W2048049573 countsByYear W20480495732019 @default.
• W2048049573 countsByYear W20480495732020 @default.
• W2048049573 countsByYear W20480495732021 @default.
• W2048049573 countsByYear W20480495732022 @default.
• W2048049573 countsByYear W20480495732023 @default.
• W2048049573 crossrefType "journal-article" @default.
• W2048049573 hasAuthorship W2048049573A5036208317 @default.
• W2048049573 hasAuthorship W2048049573A5065907624 @default.
• W2048049573 hasAuthorship W2048049573A5068803496 @default.
• W2048049573 hasAuthorship W2048049573A5090517096 @default.
• W2048049573 hasConcept C115961682 @default.
• W2048049573 hasConcept C121332964 @default.
• W2048049573 hasConcept C153180895 @default.
• W2048049573 hasConcept C154945302 @default.
• W2048049573 hasConcept C168167062 @default.
• W2048049573 hasConcept C190470478 @default.
• W2048049573 hasConcept C19235068 @default.
• W2048049573 hasConcept C193435613 @default.
• W2048049573 hasConcept C204321447 @default.
• W2048049573 hasConcept C2524010 @default.
• W2048049573 hasConcept C2780861071 @default.
• W2048049573 hasConcept C28490314 @default.
• W2048049573 hasConcept C33923547 @default.
• W2048049573 hasConcept C37914503 @default.
• W2048049573 hasConcept C41008148 @default.
• W2048049573 hasConcept C546480517 @default.
• W2048049573 hasConcept C74050887 @default.
• W2048049573 hasConcept C89600930 @default.
• W2048049573 hasConcept C97355855 @default.
• W2048049573 hasConceptScore W2048049573C115961682 @default.
• W2048049573 hasConceptScore W2048049573C121332964 @default.
• W2048049573 hasConceptScore W2048049573C153180895 @default.
• W2048049573 hasConceptScore W2048049573C154945302 @default.
• W2048049573 hasConceptScore W2048049573C168167062 @default.
• W2048049573 hasConceptScore W2048049573C190470478 @default.
• W2048049573 hasConceptScore W2048049573C19235068 @default.
• W2048049573 hasConceptScore W2048049573C193435613 @default.
• W2048049573 hasConceptScore W2048049573C204321447 @default.
• W2048049573 hasConceptScore W2048049573C2524010 @default.
• W2048049573 hasConceptScore W2048049573C2780861071 @default.
• W2048049573 hasConceptScore W2048049573C28490314 @default.
• W2048049573 hasConceptScore W2048049573C33923547 @default.
• W2048049573 hasConceptScore W2048049573C37914503 @default.
• W2048049573 hasConceptScore W2048049573C41008148 @default.
• W2048049573 hasConceptScore W2048049573C546480517 @default.
• W2048049573 hasConceptScore W2048049573C74050887 @default.
• W2048049573 hasConceptScore W2048049573C89600930 @default.
• W2048049573 hasConceptScore W2048049573C97355855 @default.
• W2048049573 hasIssue "12" @default.

• next