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.

Intelligent Parallel Particle Swarm Optimization Algorithms

Abstract: Some social systems of natural species, such as flocks of birds and schools of fish, possess interesting collective behavior. In these systems, globally sophisticated behavior emerges from local, indirect communication amongst simple agents with only limited capabilities. In an attempt to simulate this flocking behavior by computers, Kennedy and Eberthart (1995) realized that an optimization problem can be formulated as that of a flock of birds flying across an area seeking a location with abundant food. This observation, together with some abstraction and modification techniques, led to the development of a novel optimization technique particle swarm optimization. Particle swarm optimization has been shown to be capable of optimizing hard mathematical problems in continuous or binary space. We present here a parallel version of the particle swarm optimization (PPSO) algorithm together with three communication strategies which can be used according to the independence of the data. Some communication strategies for PPSO are discussed in this work, which can be used according to the strength of the correlation of parameters. Experimental results confirm the superiority of the PPSO algorithms.

Robust VQ-Based digital watermarking for the memoryless binary symmetric channel

Abstract: Vector quantization (VQ) has been distinguished for its high compression rate in lossy data compression applications. And VQ-based watermarking plays a newly developed branch in digital watermarking research fields. In this paper, we propose optimized schemes for VQ-based image watermarking. We overcome the VQ index assignment problem with genetic algorithm, which is suitable for transmitting the watermarked image over noisy channels. We obtain better robustness of the watermarking algorithm against the effects caused by channel noise in our simulations after inspecting the results from several test images. In addition, to compare with existing schemes in literature, the watermarked image quality in our scheme has approximately the same quality, with better performance in robustness, to the schemes proposed by other researchers. This also proves the effectiveness of our proposed schemes in VQ-based image watermarking for copyright protection.

Low-Complexity Digit-Serial and Scalable SPB/GPB Multipliers Over Large Binary Extension Fields Using (b,2)-Way Karatsuba Decomposition

Abstract: Shifted polynomial basis (SPB) and generalized polynomial basis (GPB) are two variations of polynomial basis representation. SPB/GPB have potential for efficient bit-level and digit-level implementations of multiplication over binary extension fields. This paper presents a (b,2)-way KA decomposition for digit-serial multiplication with low-space complexity. Based on the proposed parallel (b,2)-way KA scheme, we derive a novel scalable SPB/GPB multiplier. Analytical results show that the proposed multiplier could achieve the desired trade-off between space and time complexities. Our proposed multiplier is modular, regular, and suitable for very-large-scale integration (VLSI) implementations. It involves significantly less area complexity, less computation time and less energy consumption compared to the existing digit-serial and scalable multipliers.

Neighborhood Feature Line Segment for Image Classification

Abstract: In this paper, two improved classifiers based on the nearest feature line (NFL) are proposed for image classification, where the neighborhood feature line segment-I (NFLS-I) classifier uses the neighborhood of prototypes to select the better-fitted feature lines (FLs) and the neighborhood feature line segment-II (NFLS-II) classifier utilizes the neighborhood of the query sample to choose more-likely FLs. With better selection of FLs, these two classifiers can both improve the recognition performance and the computation problem. A large number of experiments on Soil-100 object database, Yale face database, FEI face database, AR face database, and Jochen triesch static hand posture database are performed to evaluate these two proposed classifiers. The experimental results demonstrate that the proposed NFLS-I and NFLS-II classifiers outperform the original NFL and some other improved NFL classifiers for object recognition, hand posture recognition, and face recognition.

Mean shift: a robust approach toward feature space analysis

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.

Digital Watermarking

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.

PORs: Proofs of Retrievability for Large Files

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.