CBIR Using DCT for Feature Vector Generation
Vibha Bhandari · 2012
The focus of this work is on using transformation technique for searching, browsing and retrieving images from a large database. In this paper we are using Discrete Cosine Transform to generate the feature vector .Here we are considering DCT of each R, G and B components of an image. The proposed work experimented over a database of 800 images spread across 8 classes of images. Euclidian distances between the feature vectors of query image and the database images are considered. Images are retrieved in ascending order of Euclidian distances. The Average precision and Average recall of each class and overall average of all averages of each class are calculated as a performance measure.