caa a22 4500 605446970 CHVBK 20210128100130.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s11042-014-2148-2 doi (NATIONALLICENCE)springer-10.1007/s11042-014-2148-2 Iterated local search optimized hashing for image copy detection [Elektronische Daten] [Lingyu Yan, Hefei Ling, Fuhao Zou, Cong Liu] Currently, researches on content based image copy detection mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large number of images, which is very time-consuming and unscalable. Hence, we need to pay much attention to the efficiency of image detection. Although many hashing methods has been proposed, they did not show excellent performance in decreasing semantic loss during the process of hashing. In this paper, we propose a hashing based method for image copy detection, which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. To minimize the objective function, we first calculate an approximate solution through trace optimization, and then optimize the solution through Iterated Local Search(ILS) to further decrease semantic loss. Experimental results show that our approach significantly outperforms state-of-art methods. Springer Science+Business Media New York, 2014 Content based image copy detection nationallicence Robust hashing nationallicence Iterated local search nationallicence Image fingerprinting nationallicence Yan Lingyu School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China aut Ling Hefei School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China aut Zou Fuhao School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China aut Liu Cong School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China aut Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/21(2015-11-01), 9729-9746 1380-7501 74:21<9729 2015 74 11042 https://doi.org/10.1007/s11042-014-2148-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-014-2148-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yan Lingyu School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China aut NATIONALLICENCE 700 1- Ling Hefei School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China aut NATIONALLICENCE 700 1- Zou Fuhao School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China aut NATIONALLICENCE 700 1- Liu Cong School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/21(2015-11-01), 9729-9746 1380-7501 74:21<9729 2015 74 11042