Categorisation and Retrieval of Scene Photographs from JPEG Compressed Database

Abstract:

Natural image categorisation and retrieval is the main challenge for image indexing. With the increase of available images and video databases, there is a real need to, first, organise the database automatically according to different semantic groups, and secondly, to take into account these large databases where most of the data is stored in a compressed form. The global distribution of orientation features is a very powerful tool to semantically organise the database into groups, such as outdoor urban scenes, indoor scenes, ‘closed’ landscapes (valleys, mountains, forests, etc.) and ‘open’ landscapes (deserts, fields, beaches, etc.). The constraint of a JPEG compressed database is completely integrated with an efficient implementation of an orientation estimator in the DCT (Discrete Cosinus Transform) domain. The proposed estimator is analysed from different points of view (accuracy and discrimination power). The images are then globally characterised by a set of a few parameters (two or three), allowing a fast scenes categorisation and organisation which is very robust to the quantisation effect, up to a quality factor of 10 in the JPEG format.