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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Global Interior Robot Localisation by a Colour Content Image Retrieval System | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 870492 15 pages doi 10.1155 2008 870492 Research Article Global Interior Robot Localisation by a Colour Content Image Retrieval System A. Chaari 1 2 S. Lelandais 1 C. Montagne 1 and M. Ben Ahmed2 1IBISC Laboratory CNRS FRE 2873 University ofEvry 40 Rue du Pelvoux 91020 Evry Cedex France 2RIADI Laboratory National School of Computer Science University ofManouba 2010 La Manouba Tunisia Correspondence should be addressed to A. Chaari anis.chaari@ibisc.fr Received 2 October 2006 Revised 10 April 2007 Accepted 3 August 2007 Recommended by Jose C. M. Bermudez We propose a new global localisation approach to determine a coarse position of a mobile robot in structured indoor space using colour-based image retrieval techniques. We use an original method of colour quantisation based on the baker s transformation to extract a two-dimensional colour pallet combining as well space and vicinity-related information as colourimetric aspect of the original image. We conceive several retrieving approaches bringing to a specific similarity measure D integrating the space organisation of colours in the pallet. The baker s transformation provides a quantisation of the image into a space where colours that are nearby in the original space are also nearby in the output space thereby providing dimensionality reduction and invariance to minor changes in the image. Whereas the distance D provides for partial invariance to translation sight point small changes and scale factor. In addition to this study we developed a hierarchical search module based on the logic classification of images following rooms. This hierarchical module reduces the searching indoor space and ensures an improvement of our system performances. Results are then compared with those brought by colour histograms provided with several similarity measures. In this paper we focus on colour-based features to describe indoor
