Evaluating color and shape invariant image indexing for consumer photography

In this paper, indexing is used as a common framework to represent, index and retrieve images on the basis of color and shape invariants.To evaluate the use of color and shape invariants for the purpose of image retrieval, experiments have been conducted on a database consisting of 500 images of multicolored objects. Images in the database show a considerable amount of noise, specularities, occlusion and fragmentation resulting in a good representation of views from everyday life as it appears in home video and consumer photography in general.The experimental results show that image retrieval based on both color and shape invariants provides excellent retrieval accuracy. Image retrieval based on shape invariants yields poor discriminative power and worst computational performance whereas color based invariants image retrieval provides high discrimination power and best computational performance.Furthermore, the experimental results reveal that identifying multicolored objects entirely on the basis of color invariants is to a large degree robust to partial occlusion and a change in viewing position.