Abstract: A method of image retrieval from a target image collection, including segmenting a query image into two or more bands, obtaining weighted color histogram vectors for the two or more bands in the query image, and obtaining weighted color histogram vectors for two or more bands in a target image. A distance measurement is determined between the query image and the target image using the weighted color histogram vectors from corresponding bands in the query image and the target image. Bands in an image can be groups, strips, sections, regions, or the like, and can be linear bands, rectangular bands, circular bands, or the like. The bands are preferably, though not necessarily, concentric or otherwise aligned and any number of bands can be utilized. Also, content based image retrieval is provided that incorporates use of varying photo composition in different regions as a technique for improving accuracy of retrieval.

Abstract: A method, processing system and computer program product for image retrieval. In one aspect, the method includes, in a processing system: determining a query feature set for a search image, wherein the query feature set includes texture data indicative of a texture of the search image for a plurality of resolutions of the search image; determining a dissimilarity measurement between at least one query feature of the query feature set and at least one target feature of a target image set for one or more target images, wherein the dissimilarity measurement is determined at least partially based upon the dissimilarity between the texture data of the search image and one or more target images for at least some of the plurality of resolutions of the target image; and identifying one or more target images based upon the dissimilarity measurement.

Abstract: A method, processing system and computer program product for optimising a search of a collection of images. In one aspect, the method includes iteratively performing, in a processing system, steps of comparing a test search result set for a search query to a user defined expected search result set for the search query, wherein the search query includes a query feature set of a search image, each feature being associated with a weight; and adjusting one or more weights of the query feature set according to the results of the comparison to improve the similarity between the test and expected search result sets, thereby optimising a future image search of the collection of images.

Abstract: A method of image retrieval from a target image collection, including segmenting a query image into two or more bands, obtaining weighted colour histogram vectors for the two or more bands in the query image, and obtaining weighted colour histogram vectors for two or more bands in a target image. A distance measurement is determined between the query image and the target image using the weighted colour histogram vectors from corresponding bands in the query image and the target image. Bands in an image can be groups, strips, sections, regions, or the like, and can be linear bands, rectangular bands, circular bands, or the like. The bands are preferably, though not necessarily, concentric or otherwise aligned and any number of bands can be utilised. Also, content based image retrieval is provided that incorporates use of varying photo composition in different regions as a technique for improving accuracy of retrieval.

Abstract: A method, processing system and computer program product for image retrieval. In one aspect, the method includes, in a processing system: determining a query feature set for a search image, wherein the query feature set includes texture data indicative of a texture of the search image for a plurality of resolutions of the search image; determining a dissimilarity measurement between at least one query feature of the query feature set and at least one target feature of a target image set for one or more target images, wherein the dissimilarity measurement is determined at least partially based upon the dissimilarity between the texture data of the search image and one or more target images for at least some of the plurality of resolutions of the target image; and identifying one or more target images based upon the dissimilarity measurement.

Abstract: A method or system providing face verification, including obtaining a set of features from a selected image and determining if there are any faces in the selected image. If faces are determined a dominance factor is assigned to at least one face and verification of an identity of the at least one face in the selected image is attempted and a confidence score returned. In attempting to verify the identity of the at least one face any identity information is extracted from metadata associated with the selected image. Also disclosed is a method of facial image retrieval, including defining a query image set from one or more selected facial images, determining a dissimilarity measurement between at least one query feature and at least one target feature. This enables identification of one or more identified facial images from the target facial image set based on the dissimilarity measurement.