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.
3441918
Effect of Different Coding Patterns on Compressed Frequency Domain Based Universal JPEG Steganalysis
Current steganalytic schemes for JPEG steganography are in favor of extracting features in DCT (Discrete Cosine Transform) domain and/or spatial domain. A recently proposed compressed frequency domain based universal steganalytic algorithm [21] showed concern over the statistics of Huffman compressed stream. The authors claimed that it was very effective in detecting stego images embedded by JPEG steganographic tools, including JPHide, F5 and OutGuess. Even though only several bytes were embedded, the scheme was still able to work, thus demonstrating astonishing steganalysis capability. By carefully controlled studies on the factors which may have impact on the new steganalytic method, we find out the truly cause of the powerfulness of this "payload-independent" steganalyzer. Experimental results reveal that different coding patterns used in cover and stego images, rather than the Avalanche Criterion [24] explained by its authors, have led to great detection efficiency. When the same coding pattern is employed in both cover and stego images, the performance of the newly devised steganalyzer has greatly dropped. Implication from this paper is that we should ensure the difference between the cover and stego images is only caused by data embedding itself in steganography and steganalysis.
10918777
Online Signature Verification by Combining Shape Contexts and Local Features
Most parameter-based online signature verification methods achieve correspondence between the points of two signatures by minimizing the accumulation of their local feature distances. The matching based on minimizing the local feature distances alone is not adequate since the point contains not only local features but the distribution of the remaining points relative to it. One useful way to get correspondences between points on two shapes and measure the similarity of the two shapes is to use the shape context, since this descriptor can be used to describe the distributive relationship between a reference point and the remaining points on a shape. In this paper, we introduce a shape context descriptor for describing an online signature point which contains both 2D spatial information and a time stamp. A common algorithm, dynamic time warp (DTW), is used for the elastic matching between two signatures. When combining shape contexts and local features, we achieve better results than when using only the local features. We evaluate the proposed method on a signature database from the First International Signature Verification Competition (SVC2004). Experimental results demonstrate that the shape context is a good feature and has available complementarity for describing the signature point. The best result by combining the shape contexts and the local features yields an Equal Error Rate (EER) of 6.77% for five references.
206600042
Multiagent Reinforcement Learning for a Planetary Exploration Multirobot System
In a planetary rover system called “SMC rover”, the motion coordination between robots is a key problem to be solved. Multiagent reinforcement learning methods for multirobot coordination strategy learning are investigated. A reinforcement learning based coordination mechanism is proposed for the exploration system. Four-robot climbing a slope is studied in detail as an instance. The actions of the robots are divided into two layers and realized respectively, which simplified the complexity of the climbing task. A Q-Learning based multirobot coordination strategy mechanism is proposed for the climbing mission. An OpenGL 3D simulation platform is used to verify the strategy and the learning results.
35117974
Online signature verification based on null component analysis and principal component analysis
This paper describes a method for stroke-based online signature verification using null component analysis (NCA) and principal component analysis (PCA). After the segmentation and flexible matching of the signature, we extract stable segments from each reference signature in order that the segment sequences have the same length. The reference set of feature vectors are transformed and separated into null components (NCs) and principal components (PCs) by K-L transform. Online signature verification is a special two-category classification problem and there is not a single available forgery set in an actual system. Therefore, it is different from the typical application of PCA in pattern recognition that both NCA and PCA are used to respectively analyze stable and unstable components of genuine reference set. Experiments on a data set containing a total 1,410 signatures of 94 signers show that the NCA/PCA-based online signature verification method can achieve better results. The best result yields an equal error rate of 1.9%.
25955132
A new synchronization algorithm for VHDL-AMS simulation
VHDL-AMS is the Analog and Mixed-Signal Extensions to VHDL. The paper gives a brief overview of the added features to VHDL. A mixed-signal simulator has been developed based on VHDL-AMS. A new synchronization algorithm is adopted in the simulator. Using the new algorithm the analog kernel does not need to synchronize the digital kernel at each digital event time point. The efficiency of the new synchronization algorithm is tested by examples. Simulation results show the newly developed algorithm can speed up the simulation.
38238585
Exploiting multi-scale support vector regression for image compression
Unlike traditional neural networks that require predefined topology of the network, support vector regression (SVR) approach can model the data within the given level of accuracy with only a small subset of the training data, which are called support vectors (SVs). This property of sparsity has been exploited as the basis for image compression. In this paper, for still image compression, we propose a multi-scale support vector regression (MS-SVR) approach, which can model the images with steep variations and smooth variations very well resulting in good performance. We test our proposed MS-SVR based algorithm on some standard images. The experimental results verify that the proposed MS-SVR achieves better performance than standard SVR. And in a wide range of compression ratio, MS-SVR is very close to JPEG in terms of peak signal-to-noise ratio (PSNR) but exhibits better subjective quality. Furthermore, MS-SVR even outperforms JPEG on both PSNR and subjective quality when the compression ratio is higher enough, for example 25:1 for Lena image. Even when compared with JPEG-2000, the results show greatly similar trend as those in JPEG experiments, except that the compression ratio is a bit higher where our proposed MS-SVR will outperform JPEG-2000.