Title :
Image Retrieval Based on NSCT from the Science and Technology Resource Image Database
Author :
Yuehui, Ma ; Peng, Geng ; JianHua, Liu ; Yan, Jiao
Author_Institution :
Electr. & Electron. Dept., Shijiazhuang Railway Inst., Shijiazhuang, China
Abstract :
Considering the characteristics of science and technology resources image, the system structure of image retrieval techniques from the science and technology resources image database is designed to rapidly and effectively retrieve the image from the database. Firstly, a novel image retrieval algorithm based on texture is proposed. The algorithm proposed takes fully the advantage of statistical attribution of image´s nonsubsampled contourlet transform (NSCT) coefficients to form the eigenvector for depicting textural feature and shape feature. Finally, the TBIR method is used to retrieve the image from the database. Secondly the CBIR method is used to retrieve the image from the result of the TBIR method. Moreover, the three key technologies, the image segmentation, the feature extraction and the similarity measurement, is researched and comprehensively used to retrieve the image.
Keywords :
feature extraction; image retrieval; image segmentation; image texture; natural sciences computing; statistical analysis; transforms; visual databases; eigenvector; feature extraction; image retrieval; image segmentation; nonsubsampled contourlet transform; science and technology resource image database; shape feature; similarity measurement; statistical attribution; textural feature; Content based retrieval; Feature extraction; Image coding; Image databases; Image retrieval; Information retrieval; Internet; Rail transportation; Shape; Spatial databases; NSCT; NSDFB; NSP; feature extraction; image retrieval;
Conference_Titel :
Future Information Technology and Management Engineering, 2009. FITME '09. Second International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-5339-9
DOI :
10.1109/FITME.2009.20