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Jeng-Shyang Pan

Bio: Jeng-Shyang Pan is an academic researcher from Shandong University of Science and Technology. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 50, co-authored 789 publications receiving 11645 citations. Previous affiliations of Jeng-Shyang Pan include National Kaohsiung Normal University & Technical University of Ostrava.


Papers
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Journal ArticleDOI
23 Apr 2020-Sensors
TL;DR: A new intelligent computing algorithm named Enhanced Black Hole (EBH) is proposed to which the mutation operation and weight factor are applied and shows better results than the original Black Hole algorithm.
Abstract: In this paper, a new intelligent computing algorithm named Enhanced Black Hole (EBH) is proposed to which the mutation operation and weight factor are applied. In EBH, several elites are taken as role models instead of only one in the original Black Hole (BH) algorithm. The performance of the EBH algorithm is verified by the CEC 2013 test suit, and shows better results than the original BH. In addition, the EBH and other celebrated algorithms can be used to solve node coverage problems of Wireless Sensor Network (WSN) in 3-D terrain with satisfactory performance.

22 citations

Proceedings ArticleDOI
28 Oct 2002
TL;DR: Wang et al. as discussed by the authors proposed a new algorithm for digital image watermarking based on the characteristics of vector quantization (VQ) to embed multiple watermarks for copyright protection.
Abstract: We propose a new algorithm for digital image watermarking based on the characteristics of vector quantization (VQ). In contrast with the conventional watermark embedding algorithms to embed only one watermark at a time into original source, we present an algorithm to embed multiple watermarks for copyright protection. The embedding and extraction processes are efficient for implementing with the conventional VQ techniques. After embedding, the embedder would output one watermarked reconstruction image and secret keys associated with the embedded watermarks. These secret keys are then registered to the third party to preserve the ownership of the original source in order to prevent attackers from inserting counterfeit watermarks. Simulation results show that if there are some intentional attacks, all the watermarks could survive to protect the copyright. Therefore, we are able to claim robustness, usefulness, and ease of implementation of our algorithm.

22 citations

Journal ArticleDOI
TL;DR: A new load balancing method combined with the advantage of online and offline load balancing algorithms are proposed in this paper and good performance shows the efficiency of the proposed method.
Abstract: Cloud Computing (CC) makes it possible for a common user to get an access to large pools of data and computational resources through a variety of interfaces. Among the so many important problems in CC, load balancing technique has been paid more and more attention for its important role. Good load balance algorithms can make whole system run more efficient. A new load balancing method combined with the advantage of online and offline load balancing algorithms are proposed in this paper. Two-choice algorithm and its improvement are used in the online step. Bacteria Foraging Optimization (BFO) and its improvement motivated by Lamarck Evolutionary Theory are introduced in our offline step. Online load balancing uses imperfect information, aiming at finishing tasks as fast as possible; while the offline makes full use of all information to make a supplement. Experiments on the heterogeneous tasks and serving points for computation intensive loads have been used here and the good performance shows the efficiency of our proposed method.

22 citations

Proceedings Article
01 Oct 2012
TL;DR: A comprehensive survey on face recognition from practical applications, sensory inputs, methods, and application conditions, and a comprehensive survey of face recognition methods from the viewpoints of signal processing and machine learning.
Abstract: Face recognition has the wide research and applications on many areas. Many surveys of face recognition are implemented. Different from previous surveys on from a single viewpoint of application, method or condition, this paper has a comprehensive survey on face recognition from practical applications, sensory inputs, methods, and application conditions. In the sensory inputs, we review face recognition from image-based, video-based, 3D-based and hypersprectral image based face recognition, and a comprehensive survey of face recognition methods from the viewpoints of signal processing and machine learning are implemented, such as kernel learning, manifold learning method. Moreover we discuss the single training sample based face recognition and under the variable poses. The prominent algorithms are described and critically analyzed, and relevant issues such as data collection, the influence of the small sample size, and system evaluation are discussed

22 citations

Journal ArticleDOI
TL;DR: A novel image authentication scheme which can protect the image integrity of the compressed images for block truncation coding (BTC) by using reference matrix– RMB is proposed.
Abstract: A novel image authentication scheme which can protect the image integrity of the compressed images for block truncation coding (BTC) is proposed in this paper. In the proposed scheme, the authentication codes are embedded into the the quatization levels of each BTC-compressed image block by using reference matrix--- RMB. The size of the authentication codes can be decided according to the user's requirement by adjusting the value of B in Reference Matrix. The experimental results demonstrate that the proposed method outperforms previous approaches in image quality of the embedded image and high detecting accuracy.

22 citations


Cited by
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Journal ArticleDOI
TL;DR: It is proved the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density.
Abstract: A general non-parametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic computational module of the technique is an old pattern recognition procedure: the mean shift. For discrete data, we prove the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density. The relation of the mean shift procedure to the Nadaraya-Watson estimator from kernel regression and the robust M-estimators; of location is also established. Algorithms for two low-level vision tasks discontinuity-preserving smoothing and image segmentation - are described as applications. In these algorithms, the only user-set parameter is the resolution of the analysis, and either gray-level or color images are accepted as input. Extensive experimental results illustrate their excellent performance.

11,727 citations

Book
24 Oct 2001
TL;DR: Digital Watermarking covers the crucial research findings in the field and explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied.
Abstract: Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

2,849 citations

Proceedings Article
01 Jan 1999

2,010 citations

Posted Content
TL;DR: This paper defines and explores proofs of retrievability (PORs), a POR scheme that enables an archive or back-up service to produce a concise proof that a user can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.
Abstract: In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.

1,783 citations