Efficient image database filtering using colour vector techniques

With the widespread availability of personal computers and the staggering amount of digital imagery available, recent investigation has focused on the storage, query and retrieval of images from large image databases. Methods, which are employed presently, precompute image indices, which are deemed to be statistical representations of image information. Queries of colour, shape, texture, etc., are then performed directly on these indices to find valid images. The authors propose a new indexing technique which calculates the multidimensional histogram of the directional detail in a given image. They apply wavelet theory and multiresolution analysis to extract the directional information from an image and then map this information into 3-dimensional vectors. Histograms of these vectors are then calculated at different levels of resolution, allowing progressive image query using colour histogram techniques to be directly applied. The technique is capable of querying and searching a database for images based on attributes such as smoothness, randomness and horizontal, vertical and diagonal edges at varying resolutions.