Name
Abstract | ||
|---|---|---|
Insignia identification is an important task especially as a self help application on mobile phones which can be used in museums. We propose a knowledge driven rule-based approach and a learning based approach using artificial neural network (ANN) for insignia recognition. Both the approaches are based on a common set of insignia image segmentation followed by extraction of simple, yet effective features. The features used are based on one of frugal processing and computing to suit the mobile computing power. In both the approaches we identify each extracted segment in the insignia; the correct recognition of the segment followed by post processing results in the identification of the insignia. Experimental results show that both approaches work equally well in terms of recognition accuracy of over 90% in terms of identification of the segments and 100% in terms of the actual insignia identification. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-04960-1_50 | ADVANCES IN SIGNAL PROCESSING AND INTELLIGENT RECOGNITION SYSTEMS |
Field | DocType | Volume |
Mobile computing,Computer vision,Automatic image annotation,Insignia,Computer science,Image segmentation,Artificial intelligence,Mobile phone,Artificial neural network,Machine learning | Conference | 264 |
ISSN | Citations | PageRank |
2194-5357 | 0 | 0.34 |
References | Authors | |
2 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nitin Mishra | 1 | 0 | 0.68 |
| Sunil Kumar Kopparapu | 2 | 42 | 25.18 |