tailieunhanh - Báo cáo hóa học: " Interactive Exploration for Image Retrieval Matthieu Cord"

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: Interactive Exploration for Image Retrieval Matthieu Cord | EURASIP Journal on Applied Signal Processing 2005 14 2173-2186 2005 Hindawi Publishing Corporation Interactive Exploration for Image Retrieval Matthieu Cord ETIS CNRS UMR 8051 6 avenue du Ponceau 95014 Cergy-Pontoise Cedex France Email cord@ Sylvie Philipp-Foliguet ETIS CNRS UMR 8051 6 avenue du Ponceau 95014 Cergy-Pontoise Cedex France Email philipp@ Philippe-Henri Gosselin ETIS CNRS UMR 8051 6 avenue du Ponceau 95014 Cergy-Pontoise Cedex France Email gosselin@ Jerome Fournier ETIS CNRS UMR 8051 6 avenue du Ponceau 95014 Cergy-Pontoise Cedex France Email jerfournier@ Received 15 January 2004 Revised 8 February 2005 We present a new version of our content-based image retrieval system RETIN. It is based on adaptive quantization of the color space together with new features aiming at representing the spatial relationship between colors. Color analysis is also extended to texture. Using these powerful indexes an original interactive retrieval strategy is introduced. The process is based on two steps for handling the retrieval of very large image categories. First a controlled exploration method of the database is presented. Second a relevance feedback method based on statistical learning is proposed. All the steps are evaluated by experiments on a generalist database. Keywords and phrases image retrieval indexing statistical learning classification relevance feedback. 1. INTRODUCTION The recent domain of image retrieval in large databases has induced a revision of the topics of image processing and pattern recognition. Image retrieval and extraction of visual information from image databases are useful in many applications. Even if there are many different application contexts two kinds of search are usually distinguished 1 target search and category search. Target search aims at retrieving one or a few particular images in the database. Category search aims at retrieving all the images belonging to a given category. In the latter case .