Supervised and Unsupervised Image Categorization |
Author(s): |
| Pinki , Department of Computer Science and Applications, Kurukshetra university, Kurukshetra; Girdhar Gopal, Department of Computer Science and Applications, Kurukshetra university, Kurukshetra |
Keywords: |
| Image categorization, supervised classification, unsupervised categorization |
Abstract |
|
Categorization of images is a way of grouping images according to their similarity. Images categorization uses various features of images like texture, color component, shape, edge, etc. Categorization process has various steps like image pre-processing, object detection, object segmentation, feature extraction and object classification. There are basically two methods of categorization-Supervised and Unsupervised. There are various algorithms that are used to categorize image data such as K-means, ISODATA, Artificial Neural Network (ANN), Decision Tree (DT), Support Vector Machine (SVM) and Fuzzy Classification and K-Nearest Neighbor (KNN). In this paper supervised and unsupervised techniques for image categorization are discussed. |
Other Details |
|
Paper ID: IJSRDV3I40559 Published in: Volume : 3, Issue : 4 Publication Date: 01/07/2015 Page(s): 1192-1194 |
Article Preview |
|
|
|
|
