Remote Sensing Image Retrieval with Combined Features Of Salient Region

The image retrieval results(Dinosaurs) using different techniques (a) The retrieval based on HSV color+GLCM texture (b) The retrieval based on HSV color + GLCM texture of

The main objective of the proposed system to provide an efficient tool for efficient image retrieval from a huge content of image database using features based on

A new feature extraction method based on co-occurrence matrix for texture features, average RGB for color features and geometric moment for shape features.. Retrieval of

The subject of image retrieval is discussed intensively in the literature. The success of using BoVW model had also contributed to increasing the number of

Clustering results as well as the information obtained from clusters may vary with the use of different image features and parameters settings of clustering algorithms.. CT images

There are 3 parameters setting in the experiments which are the number of colour cluster that used as the colour representation of the image, the color cluster object distance

Initial search based on a query image and the selection of a representative group of images are realized by using three types low level features: color, texture and shape..

a) Dual Models: Geometric features record the highest results when combined with texture or chromatic features for the two different types of databases. The best accuracy