Face Image Retrieval with HSV Color Space using Clustering Techniques

The main objective of this paper is to classify the face images using HSV color features and an image retrieval system (CBIR) is presented which can retrieve facial images from the extracted facial features. The primary principle of CBIR in retrieving the face images is to retrieve almost all relevant images as well as to minimize the number of irrelevant images. This can be achieved with the help of clustering algorithm. When a query image is searched, the first step is determining the nearest cluster and the second step involves the computation of the distances between the query image and the target images assigned to the corresponding cluster. Finally, images that are similar to the query image are retrieved and displayed. The experiment result is compared with Euclidean distance metric where the clustering technique produces accurate image retrieval and better classification of images.