A novel technique for location independent object based image retrieval

This paper proposes an approach of object based image retrieval to retrieve the images based on location independent region of interest (ROI). In this approach, instead of extracting the features of the whole query image, features of the objects of interest are extracted. For this, some morphological operations are performed on the image. First, background subtraction is performed to reduce the effect of background intensities, then segmentation is performed and the regions are extracted. To minimize the number of comparisons in image retrieval process, the image is categorized into texture and non texture regions. This reduces the retrieval time by comparing the ROI on the basis of its category. During the feature extraction process, a flag is set to indicate the category of the image i.e. texture image or non-texture (natural) image. Feature vector of an image is stored along with respective objects within the image. Tetrolet transform is used to retrieve the texture features for the texture regions while moment invariants and edge features are used for non-texture regions. The performance and efficiency of the proposed system is tested on COREL and CIFAR databases. Experimental results show that the retrieval performance of the proposed algorithm is better in comparison to other state-of-the-art methods.