The upper and lower bounds of the information-hiding capacity of digital images

The information-hiding capacity of a digital image is the maximum information that can be hidden in that image, while the lower limit of information hiding is the minimum detectable information capacity. This paper proposes a new method of information-hiding capacity bounds analysis that is based on the neural network theories of attractors and attraction basins. With this method, the processes for determining upper and lower limits of information hiding, are unified within a single theoretical framework. Results of research show that the theory of attraction basins of neural networks can be used to determine the upper limit of information hiding and the theory of attractors of neural networks can be used to determine the lower limit of information hiding.     

Measure of circularity for parts of digital boundaries and its fast computation

This paper focuses on the design of an effective method that computes the measure of circularity of a part of a digital boundary. An existing circularity measure of a set of discrete points, which is used in computational metrology, is extended to the case of parts of digital boundaries. From a single digital boundary, two sets of points are extracted so that the circularity measure computed from these sets is representative of the circularity of the digital boundary. Therefore, the computation consists of two steps. First, the inner and outer sets of points are extracted from the input part of a digital boundary using digital geometry tools. Next, the circularity measure of these sets is computed using classical tools of computational geometry. It is proved that the algorithm is linear in time in the case of convex parts thanks to the specificity of digital data, and is in O(nlogn) otherwise. Experiments done on synthetic and real images illustrate the interest of the properties of the circularity measure.     

Efficient lower and upper bounds of the diagonal-flip distance between triangulations

There remains today an open problem whether the rotation distance between binary trees or equivalently the diagonal-flip distance between triangulations can be computed in polynomial time. We present an efficient algorithm for computing lower and upper bounds of this distance between a pair of triangulations.     

New lower and upper bounds for the competitive ratio of transmission protocols

Transmission protocols like TCP are usually divided into a time scheduling and a data selection policy. We consider on-line algorithms of data selection policies for any time scheduling policy and any routing behavior in a network. For the model introduced by Adler et al. [Proc. 5th Israel Symp. on Theory of Computing Systems, 1997, pp. 64-72], we improve both the lower and the upper bound on the competitive ratio making them asymptotically tight. Furthermore, we present a lower bound that depends on the size of the buffers that are available both to the sender and to the receiver. We obtain a constant lower bound for the competitive ratio for constant buffer size.     

Improved upper and lower bounds on the optimization of mixed chordal ring networks

Recently, Chen, Hwang and Liu [S.K. Chen, F.K. Hwang, Y.C. Liu, Some combinatorial properties of mixed chordal rings, J. Interconnection Networks 1 (2003) 3-16] introduced the mixed chordal ring network as a topology for interconnection networks. In particular, they showed that the amount of hardware and the network structure of the mixed chordal ring network are very comparable to the (directed) double-loop network, yet the mixed chordal ring network can achieve a better diameter than the double-loop network. More precisely, the mixed chordal ring network can achieve diameter about as compared to for the (directed) double-loop network, where N is the number of nodes in the network. One of the most important questions in interconnection networks is, for a given number of nodes, how to find an optimal network (a network with the smallest diameter) and give the construction of such a network. Chen et al. [S.K. Chen, F.K. Hwang, Y.C. Liu, Some combinatorial properties of mixed chordal rings, J. Interconnection Networks 1 (2003) 3-16] gave upper and lower bounds for such an optimization problem on the mixed chordal ring network. In this paper, we improve the upper and lower bounds as and , respectively. In addition, we correct some deficient contexts in [S.K. Chen, F.K. Hwang, Y.C. Liu, Some combinatorial properties of mixed chordal rings, J. Interconnection Networks 1 (2003) 3-16].     

The effects of knee angles on subjective discomfort ratings, heart rates, and muscle fatigue of lower extremities in static-sustaining tasks

The purpose of this study was to investigate the effects of knee-flexion angles on subjective discomfort ratings, heart rates, and muscle fatigue using median frequency (MDF) in a static-sustaining task. Thirty healthy participants maintained 13 postures including standing, squatting, sitting, and kneeling postures and then MDFs from the erector spinae, biceps femoris, vastus medialis, gastrocnemius, and tibialis anterior muscles, subjective discomfort, and heart rates were collected every 3 min during a sustained 15 min task. Results showed that the discomfort, heart rate and muscle fatigue were significantly influenced by the body postures. In general, standing and sitting postures showed less discomfort as well as lower heart rates, whereas squatting postures (KF120, KF90, KF60) had higher discomfort and heart rates. Three MDF change trends were reported associated with postures in this study. First, there were less changes of MDFs for standing and sitting postures; second, all patterns of MDFs for KF 150 and KF120 decreased, and lastly some MDFs had increasing trends and others showed decreasing trends for KF30, KF30T, and kneeling postures.     

Reconstruction of tomographic images from limited range projections using discrete Radon transform and Tchebichef moments

This paper presents an image reconstruction method for X-ray tomography from limited range projections. It makes use of the discrete Radon transform and a set of discrete orthogonal Tchebichef polynomials to define the projection moments and the image moments. By establishing the relationship between these two sets of moments, we show how to estimate the unknown projections from known projections in order to improve the image reconstruction. Simulation results are provided in order to validate the method and to compare its performance with some existing algorithms.     

Matching upper and lower bounds for simulations of several linear tapes on one multidimensional tape

We prove an O(t(n) ^d (t(n)) ^? / log t(n)) time bound for the sim-ulation of t(n) steps of a Turing machine using several one-dimensional work tapes on a Turing machine using one d-dimensional work tape, . We prove a matching lower bound which holds for the problem of recognizing languages on machines with a separate one-way input tape. Received: March 1995.     

Generation and recognition of digital planes using multi-dimensional continued fractions

This paper extends, in a multi-dimensional framework, pattern recognition techniques for generation or recognition of digital lines. More precisely, we show how the connection between chain codes of digital lines and continued fractions can be generalized by a connection between tilings and multi-dimensional continued fractions. This leads to a new approach for generating and recognizing digital hyperplanes.     

A novel reduced-basis method with upper and lower bounds for real-time computation of linear elasticity problems

This paper presents a novel reduced-basis method for analyzing problems of linear elasticity in a systematical, rapid and reliable fashion for solutions with both upper and lower bounds to the exact solution in the form of energy norm or compliance output. The lower bound of the solution output is obtained form the well-known reduced-basis method based on the Galerkin projection used in the finite element method, which is termed as GP_RBM. For the upper bound, a new reduced-basis approach is developed by the combination of the reduced-basis method and a smoothed Galerkin projection used in the linearly conforming point interpolation method, and it is thus termed as SGP_RBM. To examine the present SGP_RBM, we first conduct a theoretical study on the very important upper bound property. Reduced-basis models for both GP_RBM and SGP_RBM are constructed with the aid of an asymptotic error estimation and greedy adaptive procedure. The GP_RBM and the newly proposed SGP_RBM are applied to analyze a cantilever beam with an oblique crack to verify the proposed RBM technique in terms of accuracy, convergence, bound properties and computational savings. Both theoretical analysis and numerical results have demonstrated that the present method is a very efficient method for real-time solutions providing exact output bounds.     

A new feature extractor invariant to intensity, rotation, and scaling of color images

This paper proposes a new method for extracting the invariant features of an image based on the concept of principal component analysis and a competitive learning algorithm. The proposed algorithm can be applied to binary, gray-level, or colored-texture images with a size greater than 256 × 256 pixels. In addition to translation, scaling, and rotation invariant extraction, the extraction of a feature invariant to color intensity can be implemented by using this method. In our experiment, the proposed method shows the capability to differentiate images having the same shape but different colored textures. The experimental results report the effectiveness of this technique and its performance as measured by recognition accuracy rate and computational time. These results are also compared with those obtained by classical techniques.     

Unified detection of skewed rotation,reflection and translation symmetries from affine invariant contour features

Symmetry detection is significant for object detection and recognition since symmetries are salient cues for distinguishing geometrical structures from cluttered backgrounds. This paper proposes a unified framework to detect rotation, reflection and translation symmetries simultaneously on unsegmented real-world images. The detection is performed based on affine invariant contour features, and is applicable under skewed imaging with distortions. Contours on a natural image are first matched to each other to find affine invariant matching pairs, which are then classified into three groups using a sign change criterion corresponding to the three types of symmetries. The three groups are used to vote for the corresponding symmetries: the voting for rotation utilizes a scheme of short line segments; the voting for reflection is based on a parameterization of axis equation, and the voting for translation uses a cascade-like approach. Experimental results of real-world images are provided with quantitative evaluations, validating that the proposed framework achieves desired performance.