Classification of images as a pre-processing step for image retrieval

The indexing and retrieval of images in a multimedia database can be a very time consuming process, considering the amount of visual data stored in digital video libraries (DVLs). This paper proposes a semiautomated method to categorize images into groups as a pre-processing step in order to enable faster retrieval from a DVL. The wavelet transform is used to extract low-level features such as colour, texture and shape from images. The extracted features are employed to categorize the images using a novel neural network, the self-organizing tree map. The classification results are then used to train a feed forward neural network to identify the image classes an incoming query image belongs to. Initial experiments show promising results.