15318471
Ant colony system with communication strategies
In this paper an ant colony system (ACS) with communication strategies is developed. The artificial ants are partitioned into several groups. Seven communication methods for updating the pheromone level between groups in ACS are proposed and work on the traveling salesman problem using our system is presented. Experimental results based on three well-known traveling salesman data sets demonstrate the proposed ACS with communication strategies are superior to the existing ant colony system (ACS) and ant system (AS) with similar or better running times.
172381
Robust VQ-based digital watermarking for memoryless binary symmetric channel
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.
38537152
A Digital Image Watermarking Method Based on Labeled Bisecting Clustering Algorithm
19822286
A Multi-user Based Watermarking System with Two-Security-Level Keys
This paper presents a new watermarking scheme to reduce the detection error probability through removal of local mean values of an original signal. It will be analytically proven that the removal process plays role in reducing the interference between an original signal and a watermark to be embedded. This is simply based on the orthogonality of the DC signal and the AC signal. As a result, the process improves the ability of the right detection. The proposed method is analytically and empirically evaluated with no attack as well as JPEG compression attacks.
13091217
A Parallel Particle Swarm Optimization Algorithm with Communication Strategies
Particle swarm optimization (PSO) is an alternative population-based evolutionary computation technique. It 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. The first strategy is designed for solution parameters that are independent or are only loosely correlated, such as the Rosenbrock and Rastrigrin functions. The second communication strategy can be applied to parameters that are more strongly correlated such as the Griewank function. In cases where the properties of the parameters are unknown, a third hybrid communication strategy can be used. Experimental results demonstrate the usefulness of the proposed PPSO algorithm.
45038628
Fast clustering algorithms for vector quantization
Abstract Some fast clustering algorithms for vector quantization (VQ) based on the LBG recursive algorithm are presented and compared. Experimental results in comparison to the conventional vector-quantization (VQ) clustering algorithm with speech data demonstrate that the best approach will save more than 99% in the number of multiplications, as well as considerable saving in the number of additions. The increase in the number of comparisons is moderate. An improve absolute error inequality (AEI) criterion for Euclidean distortion measure is also proposed and utilized in the VQ clustering algorithm.
768133
Performance analysis of TCP-friendly AIMD algorithms for multimedia applications
In this paper, the performance of TCP-friendly generic AIMD (Additive Increase and Multiplicative Decrease) algorithms for Web-based playback and multirate multimedia applications is investigated. The necessary and sufficient TCP-friendly condition is derived, and the effectiveness and responsiveness of AIMD are studied. Due to practical implications, a Dynamic TCP-friendly AIMD (DTAIMD) algorithm is proposed. Extensive simulation results are given to verify the derived necessary and sufficient condition, and to demonstrate the performance of the proposed DTAIMD algorithm.
1997586
Automatic multimedia cross-modal correlation discovery
Given an image (or video clip, or audio song), how do we automatically assign keywords to it? The general problem is to find correlations across the media in a collection of multimedia objects like video clips, with colors, and/or motion, and/or audio, and/or text scripts. We propose a novel, graph-based approach, "MMG", to discover such cross-modal correlations.Our "MMG" method requires no tuning, no clustering, no user-determined constants; it can be applied to any multimedia collection, as long as we have a similarity function for each medium; and it scales linearly with the database size. We report auto-captioning experiments on the "standard" Corel image database of 680 MB, where it outperforms domain specific, fine-tuned methods by up to 10 percentage points in captioning accuracy (50% relative improvement).
7197213
A Manifold Regularization Approach to Calibration Reduction for Sensor-Network Based Tracking
The ability to accurately detect the location of a mobile node in a sensor network is important for many artificial intelligence (AI) tasks that range from robotics to context-aware computing. Many previous approaches to the location-estimation problem assume the availability of calibrated data. However, to obtain such data requires great effort. In this paper, we present a manifold regularization approach known as LeMan to calibration-effort reduction for tracking a mobile node in a wireless sensor network. We compute a subspace mapping function between the signal space and the physical space by using a small amount of labeled data and a large amount of unlabeled data. This mapping function can be used online to determine the location of mobile nodes in a sensor network based on the signals received. We use Crossbow MICA2 to setup the network and USB camera array to obtain the ground truth. Experimental results show that we can achieve a higher accuracy with much less calibration effort as compared to several previous systems.
9847155
GCap: Graph-based Automatic Image Captioning
Given an image, how do we automatically assign keywords to it? In this paper, we propose a novel, graph-based approach (GCap) which outperforms previously reported methods for automatic image captioning. Moreover, it is fast and scales well, with its training and testing time linear to the data set size. We report auto-captioning experiments on the "standard" Corel image database of 680 MBytes, where GCap outperforms recent, successful auto-captioning methods by up to 10 percentage points in captioning accuracy (50% relative improvement).
1155416
Co-Localization from Labeled and Unlabeled Data Using Graph Laplacian
This paper addresses the problem of recovering the locations of both mobile devices and access points from radio signals, a problem which we call colocalization, by exploiting both labeled and unlabeled data from mobile devices and access points. We first propose a solution using Latent Semantic Indexing to construct the relative locations of the mobile devices and access points when their absolute locations are unknown. We then propose a semi-supervised learning algorithm based on manifold to obtain the absolute locations of the devices. Both solutions are finally combined together in terms of graph Laplacian. Extensive experiments are conducted in wireless local-area networks, wireless sensor networks and radio frequency identification networks. The experimental results showthat we can achieve high accuracy with much less calibration effort as compared to several previous systems.