34955127
A message-based cocktail watermarking system
A noise-type Gaussian sequence is most commonly used as a watermark to claim ownership of media data. However, only a 1 bit information payload is carried in this type of watermark. For a logo-type watermark, the situation is better because it is visually recognizable and more information can be carried. However, since the sizes and shapes of logos for different organizations are different, the flexibility of use of a logo-type watermark will certainly be degraded. We design a more flexible type of watermark, i.e., a message. Since a message is composed of a finite number of ASCII-type characters, it is by nature vulnerable to attacks. Therefore, we propose to choose a set of nonlinear Hadamard codes that has the maximum Hamming distance between any two constituent codes to replace the original ASCII-type inputs. This design will make our system much more fault-tolerant in comparison with ASCII-code based systems under direct attack. To recover an attacked Hadamard code, we use a trained backpropagation neural network to perform inexact matching. Experimental results demonstrate that our message-based cocktail watermarking system is superb in terms of robustness and flexibility.
2266632
Fast Face Detection via Morphology-Based Pre-processing
An e$cient face detection algorithm which can detect multiple faces oriented in any directions in a cluttered environment is proposed. In this paper, a morphology-based technique is "rst devised to perform eye-analogue segmentation. Next, the previously located eye-analogue segments are used as guides to search for potential face regions. Then, each of these potential face images is normalized to a standard size and fed into a trained backpropagation neural network for identi"cation. In this detection system, the morphology-based eye-analogue segmentation process is able to reduce the background part of a cluttered image by up to 95%. This process signi"cantly speeds up the subsequent face detection procedure because only 5}10% of the regions of the original image remain for further processing. Experiments demonstrate that an approximately 94% success rate is reached, and that the relative false detection rate is very low. ( 2000 Published by Elsevier Science Ltd on behalf of Pattern Recognition Society.
16804646
Mean quantization blind watermarking for image authentication
The objective of this paper is to propose an image authentication scheme, which is able to detect malicious tampering of images even they have also been incidentally distorted. By modeling incidental and malicious distortions as Gaussian distributions with small and large variances, respectively, we propose to embed a watermark in the wavelet domain by a mean quantization technique. Due to the various probabilities of tamper response at each scale, these responses are integrated to make a decision on the tampered areas. Statistical analysis is conducted and experimental results are given to demonstrate that our watermarking scheme is able to detect malicious attacks while tolerating incidental distortions.
46424681
Fast face detection via morphology-based pre-processing
Abstract An efficient face detection algorithm which can detect multiple faces oriented in any directions in a cluttered environment is proposed. In this paper, a morphology-based technique is first devised to perform eye-analogue segmentation. Next, the previously located eye-analogue segments are used as guides to search for potential face regions. Then, each of these potential face images is normalized to a standard size and fed into a trained backpropagation neural network for identification. In this detection system, the morphology-based eye-analogue segmentation process is able to reduce the background part of a cluttered image by up to 95%. This process significantly speeds up the subsequent face detection procedure because only 5–10% of the regions of the original image remain for further processing. Experiments demonstrate that an approximately 94% success rate is reached, and that the relative false detection rate is very low.
10243856
A new LDA-based face recognition system which can solve the small sample size problem
A new LDA-based face recognition system is presented in this paper. Linear discriminant analysis (LDA) is one of the most popular linear projection techniques for feature extraction. The major drawback of applying LDA is that it may encounter the small sample size problem. In this paper, we propose a new LDA-based technique which can solve the small sample size problem. We also prove that the most expressive vectors derived in the null space of the within-class scatter matrix using principal component analysis (PCA) are equal to the optimal discriminant vectors derived in the original space using LDA. The experimental results show that the new LDA process improves the performance of a face recognition system signi"cantly. ( 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
35793047
A message-based cocktail watermarking system
Abstract A noise-type Gaussian sequence is most commonly used as a watermark to claim ownership of media data. However, only a 1-bit information payload is carried in this type of watermark. For a logo-type watermark, the situation is better because it is visually recognizable and more information can be carried. However, since the sizes and shapes of logos for different organizations are different, the flexibility of use of a logo-type watermark will certainly be degraded. In this paper, a more flexible type of watermark, i.e., a message, is designed. Since a message is composed of a finite number of ASCII-type characters, it is by nature vulnerable to attacks. Therefore, we propose to choose a set of nonlinear Hadamard-codes that has the maximum Hamming distance between any two constituent codes to replace the original ASCII-type inputs. This design will make our system much more fault-tolerant in comparison with ASCII-code based systems under direct attack. To recover an attacked Hadamard code, we use a trained backpropagation neural network to perform inexact matching. The proposed Hadamard code-based message is embedded using the cocktail-watermarking scheme (IEEE Trans. Multimedia 2 (4) (2000) 209–224) for copyright protection. Experimental results demonstrate that our message-based cocktail watermarking system is superb in terms of robustness and flexibility.
9386148
Orthogonal factorizations of graphs
Let G be a graph with vertex set V(G) and edge set E(G), and let g and f be two nonnegative integer-valued functions defined on V(G) such that g(x) ≤ f(x) for every vertex x of V(G). We use dG(x) to denote the degree of a vertex x of G. A graph G is called a (g,f)-graph if g(x) ≤ dG(x) ≤ f(x) for each x ∈ V(G). Then a spanning subgraph F of G is said to be a (g,f)-factor of G if F itself is a (g,f)-graph. A (g,f)-factorization of G is a partition of E(G) into edge disjoint (g,f)-factors. Let F = {F1,F2,... ,Fm} be a factorization of G and H be a subgraph of G with m edges. If Fi, 1 ≤ i ≤ m, has exactly one edge in common with H, we say that F is orthogonal to H. In this paper it is proved that every (mg + k,mf - k)-graph contains a subgraph R such that R has a (g,f)-factorization orthogonal to a given subgraph with k edges, where m and k are positive integers with 1 ≤ k > m and g(x) ≥ 0. This result has been conjectured by Yan in Yan (Sci. China Ser. A 41(1) (1998) 48).
2240592
An extremal problem for H-linked graphs
We introduce the notion of H-linked graphs, where H is a fixed multigraph with vertices w1; . . . ;wm. A graph G is H-linked if for every choice of vertices v1; . . . ; vm in G, there exists a subdivision of H in G such that vi is the branch vertex representing wi (for all i). This generalizes the notions of k -linked, k -connected, and k-ordered graphs. Given k and n 5k þ 6, we determine the least integer d such that, for every loopless graph H with k edges and minimum degree at least two, every n-vertex graph with minimum degree at least d is H-linked. This value D1(k; n) appears to equal the least integer d 0 such that every n-vertex graph with minimum degree at least d 0 is k -connected. On the way to the proof, we extend a theorem by Kierstead et al. on the least integer d 00 such that every n-vertex graph with minimum degree at least d 00 is k-ordered. 2005 Wiley Periodicals, Inc. J Graph Theory 50: 321–339, 2005
10985120
Approximation Algorithms for the k-Clique Covering Problem
The problem of covering edges and vertices in a graph (or in a hypergraph) was motivated by a problem arising in the context of the component assembly problem. The problem is as follows: given a graph and a clique size $k$, find the minimum number of $k$-cliques such that all edges and vertices of the graph are covered by (included in) the cliques. This paper provides a collection of approximation algorithms for various clique sizes with proven worst-case bounds. The problem has a natural extension to hypergraphs, for which we consider one particular class. The $k$-clique covering problem can be formulated as a set covering problem. It is shown that the algorithms we design, which exploit the structure of this special set covering problem, have better performance than those derived from direct applications of general purpose algorithms for the set covering. In particular, these special classes of set covering problems can be solved with better worst-case bounds and/or complexity than if treated as general set covering problems.