Artificial neural networks based war scene classification using various feature extraction methods: a comparative study

Authors:
S. Daniel Madan Raja;A. Shanmugam;G. Srinitya
Affiliations:
Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India;Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India;Department of Information Technology, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India
Venue:
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
Year:
2011

Citing 10
Cited 0

On Image Analysis by the Methods of Moments

IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Image Recognition by Zernike Moments

IEEE Transactions on Pattern Analysis and Machine Intelligence
Understanding dynamic scenes

Artificial Intelligence
Indoor-Outdoor Image Classification

CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Boosting Image Orientation Detection with Indoor vs. Outdoor Classification

WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Texture segmentation using wavelet transform

Pattern Recognition Letters
Segmentation and description of natural outdoor scenes

Image and Vision Computing
Scene Classification Using a Hybrid Generative/Discriminative Approach

IEEE Transactions on Pattern Analysis and Machine Intelligence
Indoor vs. outdoor scene classification in digital photographs

Pattern Recognition
Image classification for content-based indexing

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we are trying to identify the best feature extraction method for classifying war scene from natural scene using Artificial Neural Networks. Also, we are proposed a new hybrid method for the same. For this purpose two set of image categories are taken viz., opencountry & war tank. By using the proposed hybrid method and other feature extraction methods like haar wavelet, daubechies (db4) wavelet, Zernike moments, Invariant moments, co-occurrence features & statistical moments, features are extracted from the images/scenes. The extracted features are trained and tested with Artificial Neural Networks (ANN) using feed forward back propagation algorithm. The comparative results are proving efficiency of the proposed hybrid feature extraction method (i.e., the combination of GLCM & Statistical moments) in war scene classification problems. It can be concluded that the proposed work significantly and directly contributes to scene classification and its new applications. The complete work is experimented in Matlab 7.6.0 using real world dataset.