This paper presents an investigation into the use of a mobile device as a novel interface to a content-based image retrieval system. The initial development has been based on the concept of using the mobile device in an art gallery for mining data about the exhibits, although a number of other applications are envisaged. The paper presents a novel methodology for performing content-based image retrieval and object recognition from query images that have been degraded by noise and subjected to transformations through the imaging system. The methodology uses techniques inspired from the information retrieval community in order to aid efficient indexing and retrieval. In particular, a vector-space model is used in the efficient indexing of each image, and a two-stage pruning/ranking procedure is used to determine the correct matching image. The retrieval algorithm is shown to outperform a number of existing algorithms when used with query images from the mobile device