Asian Journal of Information Technology
ISSN: Online 1993-5994ISSN: Print 1682-3915
Abstract
This study discusses the comparative study of ANN and SVM in the classification problem domain. We are classifying the static images into two categories i.e., images with cars and images with no cars. This is tested without any segmentation processes. Feed forward neural networks with backpropagation algorithm are used for paradigm of ANN. On the other hand, support vector machine with radial basis kernel function with p = 5 is used for the same image classification problem. Comparative results show that the classification rate of SVM is far better than the classification rate of ANN. Features are extracted from the static images using Multi-level wavelet decomposition method. The performance of ANN and SVM is tested in 5 different levels of decomposition. This research is carried out using real world data set.
How to cite this article:
V. Devendran , Amitabh Wahi and Hemalatha Thiagarajan . ANN and SVM Based Image Classification Using Wavelet Decomposition.
DOI: https://doi.org/10.36478/ajit.2007.1174.1180
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2007.1174.1180