基于边界和模糊集理论的三维图像分割

本文提出了一种基于边界和模糊集理论的三维图象分割方法，利用高斯－拉普拉斯算子检测出图象中各结构的边界后，通过区域增长获取感光趣结构的三维二值模板，由高斯－拉普拉斯图象和二值模板出发，利用模糊集理论，确定感兴趣结构的三维模糊模板，从而达到在体积图象中分割出感兴趣结构的目的。     

多层前馈网络在图象分割中的应用

本文提出用多层前馈网络进行基于边缘信息的图象分割,讨论了学习样本的提取步骤和网络学习的速度改进方法。实验表明,用多层前馈网络进行图象分割能获得良好的结果。     

Image segmentation towards new image representation methods

Very low bit-rate video coding has recently become one of the most important areas of image communication and a large variety of applications have already been identified. Since conventional approaches are reaching a saturation point, in terms of coding efficiency, a new generation of video coding techniques, aiming at a deeper “understanding” of the image, is being studied. In this context, image analysis, particularly the identification of objects or regions in images (segmentation), is a very important step. This paper describes a segmentation algorithm based on split and merge. Images are first simplified using mathematical morphology operators, which eliminate perceptually less relevant details. The simplified image is then split according to a quad tree structure and the resulting regions are finally merged in three steps: merge, elimination of small regions and control of the number of regions.     

用光学联合变换方法对手写汉字进行分类识别

用光学联合变换方法，结合ＣＣＤ数据采集系统，对手写汉字进行统计分类识别，通过实验得出了各类别的相关峰值范围，其实验结果良好，有较大的应用前景。     

输送带表面图像快速分割技术研究

快速图像处理是基于机器视觉的输送带在线状态监测系统的关键技术。针对输送带表面图像的分割,提出了一种快速阈值分割算法。该算法基于图像的灰度信息,具有简单、实时性好等特点。文章通过用实际图像对快速阈值分割算法与其它几种算法进行了对比,结果验证了该算法的有效性。     

客观的图象质量测度及其在分割评价中的应用

图象分割是图象分析中的关健步骤。对图象分割的评价是研究分割技术性能的有效手段,其中分割质量测度起着重要作用。本文介绍一类新的客观质量测度并对其性能进行了比较研究。另外为了验证新测度的有效性,本文提出了一种比较合理全面的分割技术分类法。在此基础上选取各类技术中有代表性的算法借助新的质量测度进行了实际评价比较并取得了有意义的结果。     

A fast iterative scheme for multilevel thresholding methods

The previously published optimal thresholding techniques based on some objective functions are very efficient in the bi-level thresholding case, but they are impractical when extended to multilevel thresholding. The reason for this is their computational complexity which grows exponentially with the number of thresholds. In this paper, an iterative scheme is proposed to render these optimal thresholding techniques more practical. The proposed algorithm starts with a bi-level thresholding, then uses the initial results to obtain higher-order thresholds. This algorithm is iterative and the convergence is proved. We also introduce some useful programming techniques to make the computation more efficient. The proposed algorithm can therefore determine the number of thresholds automatically as well as save a significant amount of computing time.     

确定CO2最小混相压力的状态方程法

混相压力是确定油藏能否采用混相驱的重要依据,测定混相压力的最好方法是细管实验法,但室内实验法测定费时费力。基于细管实验的结果,结合“混相函数”的概念,提出了一种利用组分分割和组合的方法,即将C1^＋组分分割为几种以后,对利用修正的Redlich—kwong状态方程确定CO2最小混相压力的方法进行了研究和改进,克服了原方法中重组分临界值难以确定的缺点;同时提高了温度对计算结果的敏感性。计算结果与实验结果对比表明,确定的最小混相压力误差小于5％,充分证明该方法的有效性。     

弹丸目标红外图像的阈值分割算法研究

针对红外弹丸目标图像的特点,在分析比较了几种传统的基于直方图阈值分割算法的基础上,探讨了提高该类算法实时性的途径。结合弹丸目标体积固定的特点,提出了一种基于p率直方图的快速算法。在分割效果上提高了对弹丸目标提取的准确性,在运行时间上与传统直方图阈值分割算法相比平均降低了30%以上。在Matlab环境下进行了仿真,验证了算法的有效性和实时性。     

Unsupervised Bayesian image segmentation using orthogonal series

This paper deals with the problem of unsupervised image segmentation which consists in first mixture identification phase and second a Bayesian decision phase. During the mixture identification phase, the conditional probability density function (pdf) and the a priori class probabilities must be estimated. The most difficult part is the estimation of the number of pixel classes or in other words the estimation of the number of density mixture components. To resolve this problem, we propose here a Stochastic and Nonparametric Expectation-Maximization (SNEM) algorithm. The algorithm finds the most likely number of classes, their associated model parameters and generates a segmentation of the image by classifying the pixels into these classes. The non-parametric aspect comes from the use of the orthogonal series estimator. Experimental results are promising, we have obtained accurate results on a variety of real images.