Title :
Near-duplicate image detection with cascade method
Author_Institution :
Sch. of Electr. & Inf. Eng., Liaoning Univ. of Technol., Jinzhou, China
Abstract :
In this paper, a novel scheme to tackle the task of near-duplicate image detection is presented. The scheme is based on a two-level image similarity measure strategy, which reduces the overall computational cost. The second-level similarity measure considering spatial position relationship can find the small similar objects in two images. Given two input images, which are represented with multiple local features, the proposed algorithm can assert whether the reference image is a near-duplicate of the query image or not. The algorithm is demonstrated on some image or video keyframe pairs with scale change, viewpoint change, blur, noise and spatial deformation, which are extracted from INRIA copy dataset, etc. The experimental results show that proposed algorithm is simple and effective.
Keywords :
image matching; object detection; video signal processing; blur; cascade method; image similarity measure strategy; near-duplicate image detection; noise; scale change; second-level similarity measure; spatial deformation; spatial position relationship; video keyframe pair; viewpoint change; Abstracts; Computers; Rotation measurement; Duplicate detection; epipolar geometry; image matching; local feature;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
Print_ISBN :
978-1-4673-1484-8
DOI :
10.1109/ICMLC.2012.6359497