Image retrieval using low level features of object regions with application to partially occluded images

Abstract

This paper proposes an image retrieval system using the local colour and texture features of object regions and global colour features of the image. The object regions are roughly identified by segmenting the image into fixed partitions and finding the edge density in each partition using edge thresholding and morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region and Euclidean distance measure is used for computing the distance between the features of the query and target image. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods. Also promising results are obtained for 50% and 75% occluded query images. © 2012 Springer-Verlag.