The estimation of model parameter is essentially important for an MRF image model to work well. Because the maximum likelihood estimate (MLE), which is statistically optimal, is too difficult to implement, the conventional estimates such as the maximum pseudo-likelihood estimate (MPLE), the coding method estimate (CME), and the least-squares estimate (LSE) are all based on the (conditional) pixel probabilities for simplicity. However, the conventional pixel-based estimators are not very satisfactorily accurate, especially when the interactions of pixels are strong. We therefore propose two window-based estimators to improve the estimation accuracy: the adjoining-conditional-window (ACW) scheme and the separated-conditional-window (SCW) scheme. The replacement of the pixel probabilities by the joint probabilities of window pixels was inspired by the fact that the pixels in an image present information in a joint way and hence the more pixels we deal with the joint probabilities of, the more accurate the estimate should be. The window-based estimators include the pixel-based ones as special cases. We present respectively the relationship between the MLE and each of the two window-based estimates. Through the relationships we provide a unified view that the conventional pixel-based estimates and our window-based estimates all approximate the MLE. The accuracy of all the estimates can be described by two types of superiority: the cross-scheme superiority that an ACW estimate is more accurate than the SCW estimate with the same window size, and the in-scheme superiority that an ACW (or SCW) estimate more accurate than another ACW (or SCW) estimate which uses smaller window size. The experimental results showed the two types of superiority and particularly the significant improvement in estimation accuracy due to using window probabilities instead of pixel probabilities.

In this letter, we indicate that a proposed user-friendly remote authentication scheme with smart card is insecure. The authentication scheme suffers from the replay attack. An adversity can eavesdrop valid authentication information from the communicating data, modify it, and impersonate the legitimate user to login the remote system. We also present a modified scheme to overcome this vulnerability and improve the robustness. In the modified scheme, the replay attack cannot work successfully. To crack the password from the communicating message is infeasible. Even if the password is compromised, the attacker still cannot pass the authentication and gain the authority of the legitimate user.

This paper presents an ultra-wideband amplifier embedded with band-pass filter design. The scattering parameters of a frequency-domain GaAs field effect transistor are converted into z-domain representations by employing the weighted linear least squares method. A least squares scheme is employed to obtain characteristic impedances of transmission line elements that form the amplifier having a flat gain in the passband and good fall-off selectivity in the stopband. Experimental results illustrate the validity of the proposed design method.

In this paper, we present a numerical design method for two-dimensional (2-D) FIR linear-phase (LP) quincunx filter banks (QFB) with equiripple magnitude response and perfect reconstruction (PR). The necessary conditions for the filter length of analysis filters are derived. A dual affine scaling variant (DASV) of Karmarkar's algorithm is employed to minimize the peak ripples of analysis filters and an approximation scheme is introduced to satisfy the PR constraint for the 2-D filter banks (FB). The simulation examples are included to show the effectiveness of this proposed design technique.

The approach presented in this paper was intended for extending conventional Markov random field (MRF) models to a more practical problem: the unsupervised and adaptive segmentation of gray-level images. The "unsupervised" segmentation means that all the model parameters, including the number of image classes, are unknown and have to be estimated from the observed image. In addition, the "adaptive" segmentation means that both the region distribution and the image feature within a region are all location-dependent and their corresponding parameters must be estimated from location to location. We estimated local parameters independently from multiple small windows under the assumption that an observed image consists of objects with smooth surfaces, no texture. Due to this assumption, the intensity of each region is a slowly varying function plus noise, and the conventional homogeneous hidden MRF (HMRF) models are appropriate for these windows. In each window, we employed the EM algorithm for maximum-likelihood (ML) parameter estimation, and then, the estimated parameters were used for "maximizer of the posterior marginals" (MPM) segmentation. To keep continuous segments between windows, a scheme for combining window fragments was proposed. The scheme comprises two parts: the programming of windows and the Bayesian merging of window fragments. Finally, a remerging procedure is used as post processing to remove the over-segmented small regions that possibly exist after the Bayesian merging. Since the final segments are obtained from merging, the number of image classes is automatically determined. The use of multiple parallel windows makes our algorithm to be suitable for parallel implementation. The experimental results of real-world images showed that the surfaces (objects) consistent with our reasonable model assumptions were all correctly segmented as connected regions.

Some cryptographic schemes based on the bilinear pairings were proposed recently. In this paper, we apply the pairings on elliptic curve and Elliptic Curve Cryptography to the key agreement of dynamic peer group. Each member performs authentication and contributes a secret data to negotiate a group common key by means of a binary key tree. The proposed protocol does not need a dedicated central server to perform the key agreement, and the overhead is distributed among the group members. To provide a secure dynamic group communication, the key renewing mechanism has to be included. While the member joins/leaves, the group session key will be renewed to provide the backward/forward privacy, respectively. The key renewing is much efficient because it is only confined to the keys of the key-path. The proposed protocol is flexible while the change of membership is frequent.