基于Level set方法的医学图像分割

本文引入了一种基于偏微分方程的曲线进化方法—Level set方法,通过与Fast marching方法的结合,可以实现运算速度的大大提高。同时引进了更有效的Kim提出的GMM(Group Marching Method)方法,减少了运算量,并给出了改进方法。最后,把该方法用于仿真图与医学图像分割中,获得了较好的效果。     

面向对象的CAPP系统工艺知识表达

知识是人们在长期的生活及社会实践中、科学研究及实验中积累起来的对客观世界的认识与经验。工艺知识表达是CAPP系统的重要部分。本文介绍了工艺知识的种类，同时介绍了对工艺知识进行表示与组织的几种方法。以工艺知识中的制造资源为例，着重介绍了面向对象方法的概念及其描述形式。     

基于模糊度测度和改进遗传算法的图像分割

为了利用模糊集理论进行图像分割,本文提出了一种模糊度测度函数,它衡量了背景模糊集和某一个二值图像的相似性:模糊度越小,这种相似程度越大;并且对模糊度的计算只需要进行简单的比较运算和加法运算,便于硬件实现。本文利用遗传算法求取最佳阈值,针对遗传算法的某些不足之处.我们利用精英策略和模拟退火的思想,对其做了一些修正。实验结果表明:相对于Shannon熵方法和模糊熵方法,本文方法取得了较好的分割结果,并且具有较强的抗噪声能力。     

基于复合顺序形态变换的车牌边缘检测

边缘检测是图像分割的重要环节,边缘提取的好坏直接影响了整个图像处理的效果。数学形态学用具有一定形态结构的“结构元素”去度量图像的形态,以解决图像处理和分析问题。文章通过对多种边缘检测方法的分析比较,结合高速公路路口汽车图像噪声大的特点,提出了基于复合顺序形态变换的车牌边缘检测。该方法不但能有效地改善有噪图像边缘检测的效果,鲁棒性好,而且并行快速,便于硬件实现。     

Pedestrian detection and tracking in infrared imagery using shape and appearance

In this paper, we present an approach toward pedestrian detection and tracking from infrared imagery using joint shape and appearance cues. A layered representation is first introduced and a generalized expectation-maximization (EM) algorithm is developed to separate infrared images into background (still) and foreground (moving) layers regardless of camera panning. In the two-pass scheme of detecting pedestrians from the foreground layer: shape cue is first used to eliminate non-pedestrian moving objects and then appearance cue helps to locate the exact position of pedestrians. Templates with varying sizes are sequentially applied to detect pedestrians at multiple scales to accommodate different camera distances. To facilitate the task of pedestrian tracking, we formulate the problem of shot segmentation and present a graph matching-based tracking algorithm that jointly exploits the shape, appearance and distance information. Experimental results with both OSU Infrared Image Database and WVU Infrared Video Database are reported to demonstrate the accuracy and robustness of our algorithm.     

Complex system reliability modelling with Dynamic Object Oriented Bayesian Networks (DOOBN)

Nowadays, the complex manufacturing processes have to be dynamically modelled and controlled to optimise the diagnosis and the maintenance policies. This article presents a methodology that will help developing Dynamic Object Oriented Bayesian Networks (DOOBNs) to formalise such complex dynamic models. The goal is to have a general reliability evaluation of a manufacturing process, from its implementation to its operating phase. The added value of this formalisation methodology consists in using the a priori knowledge of both the system's functioning and malfunctioning. Networks are built on principles of adaptability and integrate uncertainties on the relationships between causes and effects. Thus, the purpose is to evaluate, in terms of reliability, the impact of several decisions on the maintenance of the system. This methodology has been tested, in an industrial context, to model the reliability of a water (immersion) heater system.     

On assertion-based encapsulation for object invariants and simulations

In object-oriented programming, reentrant method invocations and shared references make it difficult to achieve adequate encapsulation for sound modular reasoning. This tutorial paper surveys recent progress using auxiliary state (ghost fields) to describe and achieve encapsulation. It also compares this technique with encapsulation in the forms provided by separation logic. Encapsulation is assessed in terms of modular reasoning about invariants and simulations.     

A reconfigurable VLSI-based double-lens tracking camera

Watching and tracking an object while seeing a much wider view is one of advantages of the eye system. We proposed and developed a tracking camera system that mimics the eyes by using double-lens modules. In the system, a wide view is captured through the wide-lens module, while the target in it is tracked and magnified through the telescopic lens module. Electronic circuits for tracking control are implemented onto the reconfigurable VLSI or FPGA in order to embed the parallelism in the tracking algorithm into the hardware. A successfully developed FPGA-based prototype performs high-speed tracking at the video-rate. This work was present in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Adding Support for Persistence to CLOS via Its Metaobject Protocol

Language-level support for object persistence frees programmers from having to confront a broad class of database issues from within their applications. By virtue of its metaobject protocol, CLOS is a language whose semantics can be tailored by individual programmers. We used the metaobject protocol to extend CLOS with support for object persistence. Our goal was to obtain a version of CLOS with persistence to which we could easily port a commercial geometric CAD modeling system. We describe the design and implementation of our persistence extension and highlight the strengths and weaknesses exhibited by the CLOS metaobject protocol during our experiment. For many aspects of the implementation we found that the metaobject protocol was ideal. In other cases we had to choose among paying a large performance penalty, extending the protocol, and bypassing the protocol by modifying the language implementation directly.     

An improved watershed algorithm based on efficient computation of shortest paths

The present paper describes a new algorithm to calculate the watershed transform through rain simulation of greyscale digital images by means of pixel arrowing. The efficiency of this method is based on limiting the necessary neighbouring operations to compute the transform to the outmost, and in the total number of scannings performed over the whole image. The experiments demonstrate that the proposed algorithm is able to significantly reduce the running time of the fastest known algorithm without involving any loss of efficiency.