Title :
Cultural Relic Image Retrieval Method Based on Features of SIFT
Author :
Wen, Chao ; Geng, Guo Hua ; Zhu, Xin Yi
Abstract :
Aiming at the cultural relic image retrieval problems in digital archaeology museum of Northwest University, an image retrieval method based on Scale Invariant Feature Transform (SIFT) features is proposed in this paper. Firstly, SIFT features of cultural relic images are extracted and Principal Component Analysis method is adopted to reduce the dimensionality, then an approximate nearest neighbor search algorithm is employed in SIFT feature points matching, Finally, for further improving the retrieval accuracy, local geometric constraint is used to control false matching feature points. The experimental result on cultural relic image database shows that this method is feasible, and the proposed method improves the performance of our cultural relic image retrieval system.
Keywords :
Cultural differences; Educational institutions; Feature extraction; Histograms; Image retrieval; Vectors; content-based image retrieval; cultural relic image; local geometric constraint; scale invariant feature transform;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2011 International Conference on
Conference_Location :
Chengdu, China
Print_ISBN :
978-1-4577-1540-2
DOI :
10.1109/ICCIS.2011.119