@article {10.3844/ajassp.2014.258.265,
article_type = {journal},
title = {SOFT COMPUTING BASED MEDICAL IMAGE RETRIEVAL USING SHAPE AND TEXTURE FEATURES},
author = {Daisy, M. Mary Helta and Selvi, S. Tamil},
volume = {11},
year = {2013},
month = {Dec},
pages = {258-265},
doi = {10.3844/ajassp.2014.258.265},
url = {https://thescipub.com/abstract/ajassp.2014.258.265},
abstract = {Image retrieval is a challenging and important research applications like digital libraries and medical image databases. Content-based image retrieval is useful in retrieving images from database based on the feature vector generated with the help of the image features. In this study, we present image retrieval based on the genetic algorithm. The shape feature and morphological based texture features are extracted images in the database and query image. Then generating chromosome based on the distance value obtained by the difference feature vector of images in the data base and the query image. In the selected chromosome the genetic operators like cross over and mutation are applied. After that the best chromosome selected and displays the most similar images to the query image. The retrieval performance of the method shows better retrieval result.},
journal = {American Journal of Applied Sciences},
publisher = {Science Publications}
}