中文分词系统的设计与实现

介绍了中文分词算法和MFC应用程序,在中文分词方面,采用双向最大匹配算法,即正向最大匹配和逆向最大匹配算法。在系统设计方面,采用MFC应用程序框架实现整个系统的可视化。建立了一个包含44 000余词条的汉语电子词典及其后台数据库,完成了一个包含有汉语电子词典和中文分词功能的应用程序。     

The interpretation of laser radar images by a knowledge-based system

This paper presents a knowledge-based system to interpret laser radar (ladar) images. The objective of this research is to detect and recognize man-made objects in outdoor scenes. Our system applies themultisensor fusion approach to multiple ladar modalities to improve both segmentation and interpretation. The segmentation modules are written in C. The knowledge-based interpretation system is constructed usingKEE and Lisp. Low-level attributes of image segments (regions) are computed by the segmentation modules and then converted to theKEE format. The interpretation system applies forward chaining in a bottom-up fashion to derive object-level interpretation from input generated by low-level processing and segmentation modules. The interpretation modules detect man-made objects from the background using low-level attributes. Segments are grouped into objects, which are then classified into predefined categories (vehicles, ground, etc.). The efficiency of the interpretation system is enhanced by transferring nonsymbolic processing tasks to a concurrent service manager (program). Experimental results using ladar data are presented.     

基于马尔可夫随机场的SAR图象目标分割

运动、静止目标获取与识别（MSTAR）计划表明，将合成孔径雷达（SAP）图象分割成目标、阴影和背景杂波区域对于从开放环境中进行目标识别是一种有效的手段。但是由于SAP图象所固有的斑点噪声的影响，传统的分割方法很难获得准确的分割。为此提出了一种基于MRF(Markov random field)模型的SAP图象分割算法。用MRF模型描述待分割图象的先验知识，利用最大似然（ML）估计从训练数据中获得图象各区域的先验概率分布，采用Bayes方法，在观测数据基础上，根据分割图象的后验分布所对应的MRF模型的条件概率，利用Metroplis采样器获得最大后验概率（MAP）准则下的图象分割。通过对MSTAR的样本目标图象应用该算法，结果表明它可以获得稳健和准确的分割效果。     

基于DM642的图像分割算法的设计与实现

给出了基于DSP的图像分割算法的实现方法,以高性能数字媒体处理器DM642为核心搭建系统平台。先用Matlab语言实现图像分割算法,再通过特定的命令加参数,以及转换程序,将该程序转化为CCS所支持的程序,经调试、编译、链接通过后,将程序下载到DSP中,完成算法在DSP中的快速实现。实验结果表明,在DSP平台中实现图像分割算法,大大提高了运算速度,对于提高图像处理的实时性和促进图像处理系统的产品化,都具有重大意义。     

Shape-Based Object Detection via Boundary Structure Segmentation

We address the problem of object detection and segmentation using global holistic properties of object shape. Global shape representations are highly susceptible to clutter inevitably present in realistic images, and thus can be applied robustly only using a precise segmentation of the object. To this end, we propose a figure/ground segmentation method for extraction of image regions that resemble the global properties of a model boundary structure and are perceptually salient. Our shape representation, called the chordiogram, is based on geometric relationships of object boundary edges, while the perceptual saliency cues we use favor coherent regions distinct from the background. We formulate the segmentation problem as an integer quadratic program and use a semidefinite programming relaxation to solve it. The obtained solutions provide a segmentation of the object as well as a detection score used for object recognition. Our single-step approach achieves state-of-the-art performance on several object detection and segmentation benchmarks.     

一种基于目标特征挖掘的带钢缺陷图像分割方法

通过分析带钢图像,挖掘缺陷图像的特征,提出一种基于目标特征挖掘的带钢缺陷图像分割方法。首先,将采集的带钢缺陷图像进行中值滤波处理;然后,通过等分图像灰度范围所确定的一系列阈值对带钢图像进行预分割,通过挖掘带钢缺陷图像的特征,以特征因子作为任务驱动,找出特征值发生突变的区间;在此突变的区间内,再按照上述方法对带钢图像缺陷存在的区域进行细分,找出面积突变点,以此确定最佳阈值,通过最佳阈值进行带钢缺陷图像分割,得到特征子图;最后将若干特征子图融合,得到带钢缺陷图像分割结果。实验结果表明,将此方法应用于带钢缺陷图像分割过程中,能够完整有效地分割出带钢缺陷区域,为带钢缺陷的视觉在线检测提供了可能性。     

Experiments in curvature-based segmentation of range data

This paper focuses on the experimental evaluation of a range image segmentation system which partitions range data into homogeneous surface patches using estimates of the sign of the mean and Gaussian curvatures. The authors report the results of an extensive testing program aimed at investigating the behavior of important experimental parameters such as the probability of correct classification and the accuracy of curvature estimates, measured over variations of significant segmentation variables. Evaluation methods in computer vision are often unstructured and subjective: this paper contributes a useful example of extensive experimental assessment of surface-based range segmentation     

Combined decision theoretic and syntactic approach to image segmentation

We present the combination of a decision theoretic and a syntactic approach to image segmentation. It is shown how statistical properties of iconic information can be systematically used to program a special architecture for parallel decision theoretic image segmentation. It is also shown how the probabilistic output of this architecture automatically provides problem dependent primitives for a subsequent syntactic phase. This phase can resolve ambiguities and incomplete segmentation results in cases where objects and background are not clearly distinct by textural and gray level properties alone. Evidence for the performance of the suggested combined approach is provided by examples from different industrial and biomedical applications.Supported by Bundesminister für Forschung und Technologie (BMfT) and AEG Ulm, Germany.     

基于进化规划的最大类间方差的图像分割算法

图像分割是计算机视觉中一个关键的技术.在分析了最大类间方差算法(Ostu算法)求阈值进行图像分割以及进化规划原理的基础上,提出了一种自动阈值选取的图像分割的算法.该算法以灰度图像的灰度最大类间方差作为适应度值,将图像分割问题看作为一个全局数值优化问题,利用进化规划全局寻优和快速计算的特点,搜索一个最佳阈值用于图像分割.最后基于实例对其与传统Ostu算法进行性能比较和效果验证.结果表明,本方法在图像分割过程中具有速度快,效果好的特点.     

基于数学形态学的图像边缘检测研究

介绍数字图像处理技术中传统的边缘检测算法和基于数学形态学的数字图像边缘检测方法。通过迭代法得到图像最佳分割阈值，然后将图像二值化，再利用数学形念学中腐蚀运算实现数字图像边缘检测。通过编写程序实现上述方法，并比较传统边缘检测算法与基于数学形态学边缘检测方法的结果。