International Journal of Soft Computing
ISSN: OnlineISSN: Print 1816-9503
Abstract
Texture analysis plays a vital role in many tasks, ranging from remote sensing to medical imaging and query by content in large image data bases. The main difficulty of texture analysis in the past was the lack of adequate tools to extract the features for classification and segmentation. Although there are many techniques available they are not capable of classifying the universal textures because of their inherent limitations. In this study, a novel approach of feature extraction by combining the texture features at multiple scales based on block by block comparison of wavelet based Laws features. The performance of this classification is superior to traditional techniques. The efficiency of the proposed method is found to be better.
How to cite this article:
S. Suresh Kumar and L. Ganesan . Texture Classification Using Wavelet Based Laws Energy Measure.
DOI: https://doi.org/10.36478/ijscomp.2008.293.296
URL: https://www.makhillpublications.co/view-article/1816-9503/ijscomp.2008.293.296