Representing the appearances of surfaces illuminated from different directions has long been an active research topic. While many representation methods have been proposed, the relationships and conversion between different representations have been less well researched. These relationships are important, as they provide (a) an insight as to the different capabilities of the surface representations, and (b) a means by which they may be converted to common formats for computer graphic applications. In this paper, we introduce a single mathematical framework and use it to express three commonly used surface texture relighting representations: surface gradients (Gradient), Polynomial Texture Maps (PTM) and eigen base images (Eigen). The framework explicitly reveals the relations between the three methods, and from this we propose a set of conversion methods. We use 26 rough surface textures illuminated from 36 directions for our experiments and perform both quantitative and qualitative assessments to evaluate the conversion methods. The quantitative assessment uses a normalized root-mean-squared error as metric to compare the original images and those produced by proposed representation methods. The qualitative assessment is based on psychophysical experiments and non-parametric statistics. The results from the two assessments are consistent and show that the original Eigen representation produces the best performance. The second best performances are achieved by the original PTM representation and the conversion between Polynomial Texture Maps (PTM) and eigen base images (Eigen), while the performances of other representations are not significantly different.

We present a new method for simultaneously determining three-dimensional (3D) motion and structure of a nonrigid object from its uncalibrated two-dimensional (2D) data with Gaussian or non-Gaussian distributions. A nonrigid motion can be treated as a combination of a rigid component and a nonrigid deformation. To reduce the high dimensionality of the deformable structure or shape, we estimate the probability distribution function (PDF) of the structure through random sampling, integrating an established probabilistic model. The fitting between the observations and the estimated 3D structure will be evaluated using the pooled variance estimator. The recovered structure is only available when the 2D feature points have been properly corresponded over two image frames. Applications of the proposed method to both synthetic and real image sequences are demonstrated with promising results.

从路口视频图像中实时地构建道路背景图像是基于背景减法的车流量检测的前提。由于路口车流信息复杂，图像受外界环境因素影响大，现有的背景估计算法都有不足之处。该文提出了一种改进的频度背景估计算法，通过离散样本图像，实时地构建背景。该方法不仅算法简单、实时性高，而且增强了在背景估计时对光线变化的适应性，提高了背景建模的准确度，可适用于基于视频的路口信号灯的智能控制系统。

A theoretical analysis of the fringe pattern produced by a capillary tube interferometer is presented, which is expected to be two-beam interference, and a computer program to simulate the interference fringe pattern is established. By comparing the simulated fringe pattern and the experimental fringe pattern, the refractive index of the liquid can be given when the two fringes coincide best. The results of this method are close to those of the Abbe refractometer.

Tissue microarray (TMA) technology allows rapid visualization of molecular targets in thousands of tissue specimens at a time and provides valuable information on expression of proteins within tissues at a cellular and sub-cellular level. TMA technology overcomes the bottleneck of traditional tissue analysis and allows it to catch up with the rapid advances in lead discovery. Studies using TMA on immunohistochemistry (IHC) can produce a large amount of images for interpretation within a very short time. Manual interpretation does not allow accurate quantitative analysis of staining to be undertaken. Automatic image capture and analysis has been shown to be superior to manual interpretation. The aims of this work is to develop a truly high-throughput and fully automated image capture and analysis system. We develop a robust colour segmentation algorithm using hue-saturation-intensity (HSI) colour space to provide quantification of signal intensity and partitioning of staining on high-throughput TMA. Initial segmentation results and quantification data have been achieved on 16,000 TMA colour images over 23 different tissue types.