Annotating Images from Large Scale Web Community
C. Ranjeeth Kumar1, Prisgal Saha G2, Sameema N3, Shruthy Raj4
1Mr. C. Ranjeeth Kumar, Department of Information Technology, Sri Ramakrishna Engineering College, Coimbatore, (Tamil Nadu), India.
2Ms. G. Prisgal Saha, Department of Information Technology, Sri Ramakrishna Engineering College, Coimbatore, (Tamil Nadu), India.
3Ms. N. Sameema, Department of Information Technology, Sri Ramakrishna Engineering College, Coimbatore, (Tamil Nadu), India.
4Ms. Shruthy Raj, Department of Information Technology, Sri Ramakrishna Engineering College, Coimbatore, (Tamil Nadu), India.
Manuscript received on 23 March 2015 | Revised Manuscript received on 30 March 2015 | Manuscript published on 30 March 2015 | PP: 65-67 | Volume-4 Issue-1, March 2015 | Retrieval Number: A1371034115©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Automatic image annotation is a process by which metadata is assigned in form of captioning or keywords to a digital image. Large annotation databases are difficult to build because some of the images have partial annotations and noise tags problem. In order to solve the problems with the annotation of large databases, in our approach we remove noise and invalid images from the dataset and extract the visual features from the images. Annotation results are improved using WordNet based annotation refinement method.
Keyword: Automatic Annotation, Classification, Feature Extraction, Tagging
Scope of the Article: Classification