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Institution

Xidian University

EducationXi'an, China
About: Xidian University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Antenna (radio) & Synthetic aperture radar. The organization has 32099 authors who have published 38961 publications receiving 431820 citations. The organization is also known as: University of Electronic Science and Technology at Xi'an & Xīān Diànzǐ Kējì Dàxué.


Papers
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Journal ArticleDOI
TL;DR: An algorithm for license plate recognition (LPR) applied to the intelligent transportation system is proposed on the basis of a novel shadow removal technique and character recognition algorithms based on the improved Bernsen algorithm combined with the Gaussian filter.
Abstract: An algorithm for license plate recognition (LPR) applied to the intelligent transportation system is proposed on the basis of a novel shadow removal technique and character recognition algorithms. This paper has two major contributions. One contribution is a new binary method, i.e., the shadow removal method, which is based on the improved Bernsen algorithm combined with the Gaussian filter. Our second contribution is a character recognition algorithm known as support vector machine (SVM) integration. In SVM integration, character features are extracted from the elastic mesh, and the entire address character string is taken as the object of study, as opposed to a single character. This paper also presents improved techniques for image tilt correction and image gray enhancement. Our algorithm is robust to the variance of illumination, view angle, position, size, and color of the license plates when working in a complex environment. The algorithm was tested with 9026 images, such as natural-scene vehicle images using different backgrounds and ambient illumination particularly for low-resolution images. The license plates were properly located and segmented as 97.16% and 98.34%, respectively. The optical character recognition system is the SVM integration with different character features, whose performance for numerals, Kana, and address recognition reached 99.5%, 98.6%, and 97.8%, respectively. Combining the preceding tests, the overall performance of success for the license plate achieves 93.54% when the system is used for LPR in various complex conditions.

291 citations

Journal ArticleDOI
TL;DR: The general architecture of big data analytics is formalized, the corresponding privacy requirements are identified, and an efficient and privacy-preserving cosine similarity computing protocol is introduced as an example in response to data mining's efficiency and privacy requirements in the big data era.
Abstract: Big data, because it can mine new knowledge for economic growth and technical innovation, has recently received considerable attention, and many research efforts have been directed to big data processing due to its high volume, velocity, and variety (referred to as "3V") challenges. However, in addition to the 3V challenges, the flourishing of big data also hinges on fully understanding and managing newly arising security and privacy challenges. If data are not authentic, new mined knowledge will be unconvincing; while if privacy is not well addressed, people may be reluctant to share their data. Because security has been investigated as a new dimension, "veracity," in big data, in this article, we aim to exploit new challenges of big data in terms of privacy, and devote our attention toward efficient and privacy-preserving computing in the big data era. Specifically, we first formalize the general architecture of big data analytics, identify the corresponding privacy requirements, and introduce an efficient and privacy-preserving cosine similarity computing protocol as an example in response to data mining's efficiency and privacy requirements in the big data era.

291 citations

Journal ArticleDOI
TL;DR: An efficient quantum private comparison protocol for comparing information of equality with the help of a third party (TP) is proposed, which can ensure fairness, efficiency and security.
Abstract: Following some ideas of the quantum secret sharing (QSS) protocol (2008, Phys. Lett. A 372, 1957), we propose an efficient quantum private comparison (QPC) protocol for comparing information of equality with the help of a third party (TP). The protocol can ensure fairness, efficiency and security. The protocol is fair, which means that one party knows the sound result of the comparison if and only if the other one knows the result. The protocol is efficient with the help of the TP for calculating. However, the TP cannot learn any information about the players' respective private inputs and even about the comparison result and cannot collude with any player. The protocol is secure for the two players, that is, any information about their respective secret inputs will not leak except the final computation result. A precise proof of security of the protocol is presented. Applications of this protocol may include private bidding and auctions, secret ballot elections, commercial business, identification in a number of scenarios and so on.

285 citations

Journal ArticleDOI
TL;DR: In this article, a compact multiple-input-multiple-output (MIMO) antenna for ultrawideband (UWB) applications is presented, which consists of two open L-shaped slot (LS) antenna elements and a narrow slot on the ground plane.
Abstract: A compact multiple-input-multiple-output (MIMO) antenna is presented for ultrawideband (UWB) applications. The antenna consists of two open L-shaped slot (LS) antenna elements and a narrow slot on the ground plane. The antenna elements are placed perpendicularly to each other to obtain high isolation, and the narrow slot is added to reduce the mutual coupling of antenna elements in the low frequency band (3-4.5 GHz). The proposed MIMO antenna has a compact size of 32 ×32 mm 2 , and the antenna prototype is fabricated and measured. The measured results show that the proposed antenna design achieves an impedance bandwidth of larger than 3.1-10.6 GHz, low mutual coupling of less than 15 dB, and a low envelope correlation coefficient of better than 0.02 across the frequency band, which are suitable for portable UWB applications.

280 citations

Journal ArticleDOI
TL;DR: This paper presents the first attribute-based keyword search scheme with efficient user revocation (ABKS-UR) that enables scalable fine-grained (i.e., file-level) search authorization and formalizes the security definition and proves the proposed AB KS-UR scheme selectively secure against chosen-keyword attack.
Abstract: Search over encrypted data is a critically important enabling technique in cloud computing, where encryption-before-outsourcing is a fundamental solution to protecting user data privacy in the untrusted cloud server environment. Many secure search schemes have been focusing on the single-contributor scenario, where the outsourced dataset or the secure searchable index of the dataset are encrypted and managed by a single owner, typically based on symmetric cryptography. In this paper, we focus on a different yet more challenging scenario where the outsourced dataset can be contributed from multiple owners and are searchable by multiple users, i.e., multi-user multi-contributor case. Inspired by attribute-based encryption (ABE), we present the first attribute-based keyword search scheme with efficient user revocation (ABKS-UR) that enables scalable fine-grained (i.e., file-level) search authorization. Our scheme allows multiple owners to encrypt and outsource their data to the cloud server independently. Users can generate their own search capabilities without relying on an always online trusted authority. Fine-grained search authorization is also implemented by the owner-enforced access policy on the index of each file. Further, by incorporating proxy re-encryption and lazy re-encryption techniques, we are able to delegate heavy system update workload during user revocation to the resourceful semi-trusted cloud server. We formalize the security definition and prove the proposed ABKS-UR scheme selectively secure against chosen-keyword attack. To build confidence of data user in the proposed secure search system, we also design a search result verification scheme. Finally, performance evaluation shows the efficiency of our scheme.

279 citations


Authors

Showing all 32362 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Jie Zhang1784857221720
Bin Wang126222674364
Huijun Gao12168544399
Hong Wang110163351811
Jian Zhang107306469715
Guozhong Cao10469441625
Lajos Hanzo101204054380
Witold Pedrycz101176658203
Lei Liu98204151163
Qi Tian96103041010
Wei Liu96153842459
MengChu Zhou96112436969
Chunying Chen9450830110
Daniel W. C. Ho8536021429
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023117
2022529
20213,751
20203,816
20194,017
20183,382