Iterated local search optimized hashing for image copy detection

Verfasser / Beitragende:
[Lingyu Yan, Hefei Ling, Fuhao Zou, Cong Liu]
Ort, Verlag, Jahr:
2015
Enthalten in:
Multimedia Tools and Applications, 74/21(2015-11-01), 9729-9746
Format:
Artikel (online)
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024 7 0 |a 10.1007/s11042-014-2148-2  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s11042-014-2148-2 
245 0 0 |a Iterated local search optimized hashing for image copy detection  |h [Elektronische Daten]  |c [Lingyu Yan, Hefei Ling, Fuhao Zou, Cong Liu] 
520 3 |a 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. 
540 |a Springer Science+Business Media New York, 2014 
690 7 |a Content based image copy detection  |2 nationallicence 
690 7 |a Robust hashing  |2 nationallicence 
690 7 |a Iterated local search  |2 nationallicence 
690 7 |a Image fingerprinting  |2 nationallicence 
700 1 |a Yan  |D Lingyu  |u School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China  |4 aut 
700 1 |a Ling  |D Hefei  |u School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China  |4 aut 
700 1 |a Zou  |D Fuhao  |u School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China  |4 aut 
700 1 |a Liu  |D Cong  |u School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China  |4 aut 
773 0 |t Multimedia Tools and Applications  |d Springer US; http://www.springer-ny.com  |g 74/21(2015-11-01), 9729-9746  |x 1380-7501  |q 74:21<9729  |1 2015  |2 74  |o 11042 
856 4 0 |u https://doi.org/10.1007/s11042-014-2148-2  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s11042-014-2148-2  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Yan  |D Lingyu  |u School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Ling  |D Hefei  |u School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Zou  |D Fuhao  |u School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Liu  |D Cong  |u School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Multimedia Tools and Applications  |d Springer US; http://www.springer-ny.com  |g 74/21(2015-11-01), 9729-9746  |x 1380-7501  |q 74:21<9729  |1 2015  |2 74  |o 11042