Proceedings Paper
The real time endoscopic image analysis| Format | Member Price | Non-Member Price |
|---|---|---|
| $17.00 | $21.00 |
Paper Abstract
A new method for endoscopic image analysis in real time is presented. This method allows improving accuracy and helps avoiding subjectivity when performing endoscopic image classification. The method is based on use of Scale– invariant feature transform detector and computation of gastric mucosa pit–pattern skeletons. Subsequent use of the “Bag of visual words” method (“Bag of features”) and K–means method for key points clustering allows image classification with more than 85% accuracy.
Paper Details
Date Published: 17 March 2017
PDF: 5 pages
Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103411E (17 March 2017); doi: 10.1117/12.2268721
Published in SPIE Proceedings Vol. 10341:
Ninth International Conference on Machine Vision (ICMV 2016)
Antanas Verikas; Petia Radeva; Dmitry P. Nikolaev; Wei Zhang; Jianhong Zhou, Editor(s)
PDF: 5 pages
Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103411E (17 March 2017); doi: 10.1117/12.2268721
Show Author Affiliations
Radi Kadushnikov, SIAMS Ltd (Russian Federation)
Dmitry Bykov, SIAMS Ltd (Russian Federation)
Dmitry Bykov, SIAMS Ltd (Russian Federation)
Sergey Studenok, Ural Federal Univ. (Russian Federation)
Vyacheslav Mizgulin, Ural Federal Univ. (Russian Federation)
Vyacheslav Mizgulin, Ural Federal Univ. (Russian Federation)
Published in SPIE Proceedings Vol. 10341:
Ninth International Conference on Machine Vision (ICMV 2016)
Antanas Verikas; Petia Radeva; Dmitry P. Nikolaev; Wei Zhang; Jianhong Zhou, Editor(s)
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