38250707
Minimizing Spatial Deformation Method for Online Signature Matching
Elastic matching is an important algorithm for online signature verification. Most of elastic matching algorithms are based on dynamic time warping(DTW). In this paper, we propose a new points matching algorithm for online signature verification. After resampling a signature with equidistant spacing, we describe the resampling point by its (3+1) demesional((3+1)D) information: 3D spatial information (x-axis, y-axis, time) and a feature vector. A soft-assign matrix and two special restrictions are introduced for recording the correspondence between two signatures. With a deterministic annealing framework, the mapping between two sets of (3+1)D signature points is achieved by minimizing the warping energy of the thin-plate spline(TPS). Experimental results demonstrate that the proposed algorithm outperforms the DTW-based matching algorithms.
34644832
On-Line Signature Verification Based on PCA (Principal Component Analysis) and MCA (Minor Component Analysis)
On-line signature verification is still an active topic in the field of biometrics. This paper proposes a novel method based on PCA (Principal Component Analysis) and MCA (Minor Component Analysis). Different from the application of PCA in other fields, both principal and minor components are used to signature verification, and MC plays a very important role. Comparing with DTW and the discriminance of Euclidean distance, the method based on PCA and MCA is better. With 1215 signatures contributed by 81 signers of which numbers of reference signatures, genuine signatures and forgeries (skilled) are 5 respectively, the EER is about 5%.
12108467
Tracking Anomalous Behaviors of Name Servers by Mining DNS Traffic
This paper seeks to quantitatively understand the nature of the current threat towards the common name servers. A new tracking technique based on statistical model is proposed to locate the anomalous name servers by analyzing the real-world DNS traffic. After summarizing the attacks towards DNS, the detection method based on associative feature analysis is presented. Experiments are conducted which highlighting both the payload anomaly and the data flow anomaly, and the experimental results reveal the efficiency of our method in detecting the anomalous behaviors of name servers.
7181717
A Biased Support Vector Machine Approach to Web Filtering
Web filtering is an inductive process which automatically builds a filter by learning the description of user interest from a set of pre-assigned web pages, and uses the filter to assign unprocessed web pages. In web filtering, content similarity analysis is the core problem, the automatic-learning and relativity-analysis abilities of machine learning algorithms help solve the above problems and make ML useful in web filtering. While in practical applications, different filtering task implies different userinterest and thus implies different filtering result. This work studies how to adjust the web filtering results to be more fit for the user interest. The web filtering result are divided into three categories: relative pages, similar pages and homologous pages according to different user interest. A Biased Support Vector Machine (BSVM) algorithm, which imports a stimulant function, uses training examples distribution n+/n−− and a user-adaptable parameter k to deal imbalancedly different classes of the pre-assigned pages, is introduced to adjust the filtering result to be best fit for the user interest. Experiments show that BSVM can greatly improve the web filtering performance.
16607650
Performance Analysis of Multi-channel DCA MAC Protocol in Cognitive Wireless Mesh Networks
The spectrum resource gets scared with the development of wireless communication. Users in cognitive wireless mesh network need to switch among multi-channels to communicate. In this paper, we propose a mathematical model of multi-channel DCA protocol in cognitive wireless mesh network. This model is based on Bernoulli and M/M/K queuing model. From the validation by compare simulation with analytical result, we can see our model and analysis is simple and accurate.
3451766
Attack LSB Matching Steganography by Counting Alteration Rate of the Number of Neighbourhood Gray Levels
In this paper, we propose a new method for attacking the LSB (least significant bit) matching based steganography. Different from the LSB substitution, the least two or more significant bit-planes of the cover image would be changed during the embedding in LSB matching steganography and thus the pairs of values do not exist in stego image. In our proposed method, we get an image by combining the least two significant bit-planes and divide it into 3x3 overlapped subimages. The subimages are grouped into four types, i.e. T 1,T 2, T 3 and T 4 according to the count of gray levels. Via embedding a random sequence by LSB matching and then computing the alteration rate of the number of elements in T 1, we find that normally the alteration rate is higher in cover image than in the corresponding stego image. This new finding is used as the discrimination rule in our method. Experimental results demonstrate that the proposed algorithm is efficient to detect the LSB matching stegonagraphy on uncompressed gray scale images.
14553676
Design and Basic Experiments of a Shape-shifting Mobile Robot for Urban Search and Rescue
The recent natural and man-made devastations have urged the research on the urban search and rescue (USAR) robot systems. This paper presents a novel shape-shifting mobile robot system named as Amoeba II (A-II) for the urban search and rescue application. It has been designed with three degrees of freedom (DOFs) and two tracked drive systems. This robot consists of two modular mobile units and a joint unit. The mobile unit is a tracked mechanism to enforce the propulsion of robot. The joint unit can transform the robot shape for getting high mobility. A-II robot not only can adapt to the environment but also can change its body corresponding to locus space. It behaves two states including the parallel state (named as II state) and the linear state (named as I state). The parallel state enables the robot with high mobility on rough ground. With the linear state the robot can climb upstairs and go through narrow space such as the pipe, cave etc. Also, the joint unit can propel the robot to roll in sidewise direction. Especially, two modular A-II robots can be connected through jointing common interfaces on the joint unit to compose a stronger shape-shifting robot, which can transform the body into four wheels-driven vehicle. Finally, the elementary experimental results validate the adaptation and its mobility
2288383
An Improved FCM Algorithm Incorporating Spatial Information for Image Segmentation
Fuzzy c-means (FCM) clustering algorithm is a popular model widely used in segmentation of magnetic imaging (MRI) data. The conventional FCM does not take into account the spatial information of image and get the unexpected results of segmentation when dealing with some MRI contaminated by noise. Considering the intensities of ideal MRI are piecewise constant, we present an improved model to fuzzy c-means algorithm using membership smoothing constraint. The proposed algorithm can reasonably use the spatial information of image and improve the accuracy of segmentation. Simulation MR brain image with different noise levels and real MR brain image are presented in the experiments. The results of experiments show better robustness of our algorithms to noise than other segmentation algorithms.
30151415
Genetic Algorithm Based-On the Quantum Probability Representation
A genetic algorithm based on the quantum probability representation (GAQPR) is proposed, in which each individual evolves independently; a new crossover operator is designed to integrate searching processes of multiple individuals into a more efficient global searching process; a new mutation operator is also proposed and analyzed. Optimization capability of GAQPR is studied via experiments on function optimization, results of experiments show that, for multi-peak optimization problem, GAQPR is more efficient than GQA[4].