Name
Abstract | ||
|---|---|---|
successful indexing/categorization of images greatly enhance the performance of content based retrieval systems by filtering out irrelevant classes. This rather difficult problem has not been adequately addressed in current image database systems. In this paper we have introduced a novel feature for classification of image data by taking the one dimensional representation of it (time series) as our input data. Here we have chosen local shape feature instead of global shape feature for the said purpose which enhances its consistency in case of distorted and mutilated shapes. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-32129-0_12 | Communications in Computer and Information Science |
Keywords | Field | DocType |
classification,data mining,quanslet | Categorization,Computer vision,Pattern recognition,Computer science,Filter (signal processing),Search engine indexing,Artificial intelligence,Content based retrieval,Image database,Contextual image classification | Conference |
Volume | ISSN | Citations |
306 | 1865-0929 | 1 |
PageRank | References | Authors |
0.38 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tusar Kanti Mishra | 1 | 18 | 4.77 |
| Arun K. Pujari | 2 | 420 | 48.20 |