细胞图像自动分割方法研究

提出一种细胞图像的自动分割与定位方法.首先将直方图分割所得二值图像的距离变换作为边缘提取的指导知识,进行细胞图像的精确分割;然后利用分割边缘点的梯度方向和几何知识确定细胞的中心.该方法既能对非重叠细胞也能对重叠细胞进行细胞的分割与定位.     

一种散斑干涉条纹的细化处理

干涉条纹的细化可以减少数据存贮量、提高处理速度,同时最重要的是提高干涉条纹的判读精度.但由于散斑干涉条纹的信噪比较低,常用的图像分割算法对干涉条纹的二值化都会存在一部分失真,针对散斑干涉条纹的灰度级成规律分布的特点,提出一种不对其采用阈值分割即把干涉条纹二值化的算法,实验结果表明此算法能较好地对一幅散斑干涉条纹图像进行细化.     

改进的EM算法在分块灰度图像二值化中的应用

识别扫描得到的文本图像首先要进行二值化处理,以去掉冗余的信息.针对二值化过程中采取固定阈值会导致图像的背景和文本不能得到有效区分的问题,提出改进的分块EM算法,并应用在文本图像的二值化过程中,有效地分离了图像中的文本和背景信息,使识别的后续阶段提取的特征能够更好地代表要识别的模式.     

智能图像处理技术在车型识别中的应用研究

提出了一种应用于视频车型识别系统中的图像预处理方法．该方法对采集到的车辆图像去模糊恢复，然后采用快速的梯度算法得到背景与车辆的边缘图像，用两幅边缘图像相减分割出车辆图像，再对图像二值化，并进行直线拟合、填充处理，最后用轮廓跟踪的方法得到完整的车辆轮廓图，从而有效提取特征参数．     

����ͼ��ֱ��ͼ�ij���ͼ���ֵ�������о�

在基于数字图像处理的车牌识别技术的研究过程中,因为车牌定位和字符分割一般都是基于车牌区域的二值化结果进行的,因此对图像的二值化是非常关键的一步,二值化的效果直接影响到后面的车牌定位以及字符分割。二值化最主要的是阈值的确定,文章对比了几种常规的车牌图像全局阈值二值化处理算法,并重点分析了最大类间方差法和KSW 最大熵法的基本原理和微机仿真结果,发现用于车辆图片是这些方法不够理想,然后提出一种新的方法—基于图像直方图波形分析的车牌图像二值化处理算法,经过大量试验证明该算法在进行车牌图像二值化处理时效果非常理想。     

细胞图像自动分割方法研究

提出一种细胞图像的自动分割与定位方法．首先将直方图分割所得二值图像的距离变换作为边缘提取的指导知识，进行细胞图像的精确分割；然后利用分割边缘点的梯度方向和几何知识确定细胞的中心．该方法既能对非重叠细胞也能对重叠细胞进行细胞的分割与定位．     

复杂背景下多目标图像分割方法研究

真实路况中的运动车辆图像进行图像分割时,图像中往往存在多个车辆车牌信息,且这些车牌信息具有尺度不一,位置随机等特点,加之光照及复杂背景的影响,如何兼顾多个车辆车牌的分割效果是车辆检测和跟踪领域亟待解决的问题.为了解决这类工程应用中的问题,需要在尺度空间下对多目标图像进行分析.因本文在前期多尺度分割模型的基础上引入视觉注意机制,利用不变性特征实现多目标的定位及最优分割尺度的选取.经大量实验测试结果表明,该算法较好地实现了图像中多个车牌图像的分割并且具有较好的分割效果.     

基于球面图像的三角网格模型分割

为了从局部形状的角度实现对三角网格模型的管理和重用,提出了一种基于球面图像的三角网格模型分割方法.通过球面参数化及球面划分,将三角网格模型的表面属性信息映射到球面图像中;利用成熟的区域生长、区域合并图像分割算法对球面图像进行分割;将球面图像的分割结果转换为三角网格模型的分割结果.实验结果表明:该分割方法可以对不均匀的低分辨率三角网格模型进行有效分割,降低了几何属性估算对分割结果的影响,不会发生过分割现象,不需要进行分割的后续处理.     

基于边缘检测及数学形态学的快速汽车车牌定位

车牌定位是汽车牌照识别系统的重要环节,定位的准确性直接影响车牌识别的准确率.文章研究了利用图像边缘及数学形态学的快速汽车车牌定位方法,首先将彩色图像灰度化,并利用Sobel算子进行图像边缘提取,然后运用数学形态学算法对二值图像进行处理,得到几个车牌候选区域,最后利用连通区域的长宽比,面积比及车牌字符水平分布特征等来准确定位车牌.实验表明,这一方法能快速准确地实现车牌定位.     

交通事件视频图像自动识别系统的研究

如何有效利用高速公路视频图像信息,实时全天候自动智能检测交通事件,提升交通管理部门应急处置能效,是当前公路视频监控亟需解决的问题．本文基于视频图像处理技术,开展交通事件自动识别算法和系统的研究：采用中值滤波、亮度缩放等图像预处理方法,提取交通视频图像的前景目标边界并抑制噪声;基于灰度阈值化方法,对车辆前景进行二值化分割处理;提出一种二值化场景图像连通区域标定算法,对交通事件前景目标进行特征提取与检测识别,并基于上述算法和识别流程开发了交通事件视频自动识别系统．试验表明,该系统对噪声干扰抑制能力较强,识别准确率较高．     

A Target-Orientated Marker Image Binarization Method for Orthopaedic Surgical Navigation System

Camera calibration is the key technique in a C-arm based orthopaedic surgical navigation system. The extraction of marker location information is a necessary step in the calibration process. Ideal marker images should possess uniform background and contain marker shadow only, but in fact marker images always possess nonuniform background and are contaminated by noise and unwanted anatomic information, making the extraction very difficult. A target-orientated marker shadow extraction method was proposed. With this method a proper threshold for marker image binarization can be determined.     

Technique based on image pyramid and bayes rule for noise reduction in unsupervised change detection

In this paper, a technique based on image pyramid and Bayes rule for reducing noise effects in unsupervised change detection is proposed. By using Gaussian pyramid to process two multitemporal images respectively, two image pyramids are constructed. The difference pyramid images are obtained by point-by-point subtraction between the same level images of the two image pyramids. By resizing all difference pyramid images to the size of the original multitemporal image and then making product operator among them, a map being similar to the difference image is obtained. The difference image is generated by point-by-point subtraction between the two multitemporal images directly. At last, the Bayes rule is used to distinguish the changed pixels. Both synthetic and real data sets are used to evaluate the performance of the proposed technique. Experimental results show that the map from the proposed technique is more robust to noise than the difference image.     

颜色在识别中的应用及关键技术研究

研究颜色在识别中的应用以及所涉及到的关键技术.主要技术包括色度图、颜色库、自适应阈值、颜色模版匹配、模糊神经网络、颜色分类器等.重点研究了适于遥感图像分类的正交坐标系的YHS(亮度,色调,饱和度)变换技术.     

ICA based speckle filtering for target extraction in SAR images using adaptive space separation

A novel approach based on independent component analysis (ICA) for speckle filtering and target extraction of synthetic aperture radar (SAR) images is proposed using adaptive space separation with weighted information entropy (WIE) incorporated. First the basis and the independent components are respectively obtained by ICA technique, and WIE of the image is computed; then based on the threshold computed from function T-WIE (threshold versus weighted-information-entropy), independent components are adaptively separated and the bases are classified accordingly. Thus, the image space is separated into two subspaces: "clean" and "noise". Then, a proposed nonlinear operator ABO is applied on each component of the 'clean' subspace for further optimization. Finally, recovery image is obtained reconstructing this subspace and target is easily extracted with binarisation. Note that here T-WIE is an interpolated function based on several representative target SAR images using proposed space separation algorithm.     

基于小波变换和自适应直方图均衡的红外图像增强

针对实际应用中红外图像的对比度较低、存在噪声的缺点,结合人的视觉特征,在已有图像增强方法的基础上,采用小波变换与自适应直方图均衡相结合的方法对红外图像进行增强.该方法不但解决了红外图像对比度低的问题,而且降低了噪声,突出了图像细节.     

Automatic Airway Deletion in Pulmonary Segmentation

A method of removing the airway from pulmonary segmentation image was proposed. This method firstly segments the image into several separate regions based on the optimum threshold and morphological operator,and then each region is labeled and noted with its mean grayscale. Therefore, most of the non-lung regions can be removed according to the tissue‘s Hounsfield units (HU) and the imaging modality. Fifially, the airway region is recognized and deleted automatically through using the priori information of its HU and size. This proposed method is tested using several clinical images, yielding satisfying results.     

Modified gray level difference-based thresholding segmentation and its application in X-Ray welding image

Thresholding is a popular image segmentation method that often requires as a preliminary and indispensable stage in the computer aided image process, particularly in the analysis of X-ray welding images. In this paper, a modified gray level difference-based transition region extraction and thresholding algorithm is presented for segmentation of the images that have been corrupted by intensity inhomogeneities or noise. Classical gray level difference algorithm is improved by selective output of the result of the maximum or the minimum of the gray level with the pixels in the surrounding, and multi-structuring of neighborhood window is used to represent the essence of transition region. The proposed algorithm could robustly measure the gray level changes, and accurately extract transition region of an image. Comparisons with other approaches demonstrate the superior performance of the proposed algorithm.     

图像分块下的隧道裂缝识别方法

针对隧道衬砌表面不均匀光照、渗水和噪声等强视觉干扰,设计了基于图像分块的隧道衬砌裂缝检测算法;根据中国西部地区的地理特征和隧道衬砌的外观病害,研制开发出一种快速、自动化的非接触式智能隧道结构物外观检测系统; 以非均匀光照下隧道图像数据集为研究对象,在图像分块的基础上提出一种适用于隧道裂缝特征提取的图像识别算法;研究了电子元件产生的噪声,并分析和总结了隧道衬砌的灾害特征;根据裂缝特征和分辨率将图像矩阵划分为适当数量的区域块,根据区域块的灰度特征将原始图像划分为目标背景区、目标病害区、病害背景区和其他区域,通过最大类间方差法和局部阈值法分割得到了隧道裂缝的粗图像,在此基础上进行了粗图像裂缝特征提取;对原始图像的每个区域块进行了对比度受限的自适应直方图均衡操作和局部阈值分割,得到了细节图像;将细节图像和粗图像的重叠区域设为理想裂缝二值化图像;结合隧道结构物外观检测系统对不同方向的裂缝图像进行了二值化试验,并通过隧道裂缝定位和投影法得到了隧道衬砌图像中裂缝的位置信息和方向。研究结果表明:提出的算法对隧道裂缝识别的准确值、召回率和F值可分别达90.34%、98.78%和94.37%,既可以保证隧道裂缝的完整性,也可以在非均匀光照下最大程度地保留目标裂缝的细节,可用于处理一般灰度图像的二值化问题。      

HIERARCHICAL CONTENT BASED IMAGE RETRIEVAL

ＩｎｔｒｏｄｕｃｔｉｏｎＡｔｒａｄｅｍａｒｋｉｍａｇｅｄａｔａｂａｓｅｉｓａｓｅｔｏｆｔｒａｄｅ－ｍａｒｋｐｉｃｔｕｒｅｓ．Ｕｓｕａｌｙｉｔｉｓｔｈｅｄｕｔｙｏｆｐａｔｅｎｔａｎｄｔｒａｄｅｍａｒｋｏｆｉｃｅｔｏｅｓｔａｂｌｉｓｈａｎｄｍａｎａｇｅｔ...     

A New Robust Image Matching Method Based on Distance Reciprocal

Object matching between two-dimensional images is an important problem in computer vision. The purpose of object matching is to decide the similarity between two objects. A new robust image matching method based on distance reciprocal was presented. The distance reciprocal is based on human visual perception. This method is simple and effective. Moreover, it is robust against noise. The experiments show that this method outperforms the Hausdorff distance, when the images with noise interfered need to be recognized.