基于Hausdorff距离的手势识别

随着先进人机交互技术的提出及发展，手势识别正成为其中一项关键技术，基于视觉的手势识别是当前涉及图象处理，模式识别，计算机视觉等领域的一个比较活跃的课题，由于Hausdorff距离模板匹配的方法具有计算量小，适应性强的特点，因此基于Hausdorff距离，建立了一个手势识别系统，该系统采用边缘特征像素点作为识别特征，并首次利用Hausdorff距离模板匹配的思想，在距离变换空间内，实现了中国手指字母集上的基于单目视觉的30个手指字母的手势识别，为提高系统的鲁棒性，还提出了修正的Hausdorff距离形式，测试集上的平均识别率为96．7％，实验结果表明，基于Hausdorff距离的模板匹配方法用于基于听觉的静态手势识别是可行的。     

基于SUSAN角点检测的动态目标识别

为了快速准确地进行车型识别,提出了一种基于SUSAN角点检测的识别方法。通过计算待识别车辆与三种标准样本SUSAN角点的Hausdorff距离,将Hausdorff距离较小的两者认定具有相同的车型,实验结果表明,该方法准确、有效且实时性较好。     

使用改进的方向滤波与修正的Hausdorff距离的指静脉识别方法

针对已有静脉识别方法存在的识别结果易受图像质量影响、计算量大的问题,提出一种使用改进的方向滤波与修正的Hausdorff距离技术的指静脉识别方法.根据指静脉图像具有的方向特性设计邻域方向模板及方向滤波器模板对图像进行滤波增强处理后,利用修正的Hausdorff距离模板匹配的思想,在距离变换空间内实现指静脉图像的匹配识别.实验结果表明,该方法对指静脉图像的匹配识别具有较好的准确率.     

图像匹配的鲁棒型Hausdorff方法

提出基于一种新型Hausdorff距离的鲁棒型图像匹配方法，首先对传统的各种Hausdorff距离所存在的缺陷进行了分析，然后根据这些缺陷提出了“鲁棒型”的Hausdorff距离，这一新的距离考虑了边缘点的位置，边缘点的总数，由有限点组成的伪边缘，出格点和边缘的遮挡等因素，从而使传统的缺陷得到了克服，对合成图像及实际图像的实验结果表,暖气 提出的Hausdorff距离测度比传统的Hausdorff距离测度更为有效。     

基于图像匹配技术的飞机识别

从图像匹配原理着手，采用了3种模板匹配方法：基于德耳塔相关度量，基于改进Hausdorff距离算法和基于序贯相似性检测算法，对机场飞机进行匹配和识别。实验结果证明了这3种方法的有效性。     

一种快速实用的车牌字符识别方法

提出了一种新的车牌字符识别算法.该方法先对车牌中的单个字符进行预处理,然后采用Hausdorff距离模板匹配方法识别,对于特定位置的特殊字符,再进行校正识别.实验表明,该方法有效可行。     

基于Hausdorff距离的插值方法评价

在图像放大处理中通常要将图像进行插值,在Hausdorff测度理论的基础上对Hausdorff距离进行了改进．然后将改进后的Haosdorff距离作为评价图像质量的一种标准，对放大后的图像进行量化评估,并与其他的评价方法进行比较．结果表明用Hausdorff距离作为评价标准得到的结果更接近图像的视觉效果.     

基于外耳轮廓边缘信息的人耳识别

提出一种用Hausdorff距离表示入耳边缘特征的人耳识别方法.首先对原始人耳图像进行预处理,用基于灰度形态学梯度和局部阈值分割的边缘检测方法提取外耳轮廓边缘;然后用标准方差和边缘线段间长度差改进的Hausdorff距离表示人耳特征向量;最后采用支持向量机算法完成人耳识别.实验结果证明,该方法能获得更高的人耳识别率.     

利用Hausdorff距离人脸图像定位算法

利用 Hausdorff距离的人脸图像定位算法是动态人脸识别系统的预处理工作 .定位算法与识别系统相结合 ,可提高人脸识别率 .由于动态人脸图像在移动过程中成像大小不是完全相同的 ,这样对进一步运动中人脸图像相互关系有较大的影响 ,提出了利用 Hausdorff距离来对图像中人脸进行定位 ,将图像中人脸部分提取出来并对其大小做调整 ,过滤掉背景信息 ,一定程度上简化了后续识别工作     

基于Hausdorff距离的飞机定位方法

为了更快、更准确地识别出遥感图像中的飞机目标,用角点与Hausdorff距离相结合的方法来定位飞机目标.首先对图像进行Harris角点提取,由于传统的Harris角点提取方法对尺度比较敏感,所以采用Harris-Laplacian角点提取方法,由于在尺度空间的每层图像上计算Harris角点的计算量比较大,结合机场图像背景单一且飞机的灰度值比较高的特殊性,提高角点检测的速度和准确性;然后利用改进的Hausdorff距离即基于平均距离值的Hausdorff距离对两个特征点集进行匹配来定位飞机目标.该方法只需要一个模板就能对飞机目标进行定位.通过对机场图像的试验结果表明,该方法能很好地定位出飞机目标,具有较好的鲁棒性和实用性.     

Towards historical document indexing: extraction of drop cap letters

This paper deals with the difficult problem of indexing ancient graphic images. It tackles the particular case of indexing drop caps (also called Lettrines) and specifically, considers the problem of letter extraction from this complex graphic images. Based on an analysis of the features of the images to be indexed, an original strategy is proposed. This approach relies on filtering the relevant information, on the basis of Meyer decomposition. Then, in order to accommodate the variability of representation of the information, a Zipf’s law modeling enables detection of the regions belonging to the letter, what allows it to be segmented. The overall process is evaluated using a relevant set of images, which shows the relevance of the approach.     

图形编辑及图形在文档和电子邮件中的插入方法

在Windows之下的WORD或其它文本编辑软件中进行文稿编辑时,经常遇到插入图形图象的问题,甚至在电子邮件Email中编辑发送函件也同样有这种可能。介绍文档及电子邮件中图形图片的编辑、插入等处理方法,简单实用。     

Grey level thresholding using second-order statistics

This letter describes algorithms for global thresholding of grey-tone images which use second-order grey level statistics. Two measures of interaction between classes of intensity levels are defined on simple co-occurance matrices and are used to evaluate and select thresholds. One of these measures is seen to be independent of the grey level histogram and effective in selecting thresholds for images with unimodal grey level distributions. The algorithms are also used for multithresholding without modifications.     

Robust algorithm for tunnel closing in 3D volumetric objects based on topological characteristics of points

In this letter, we propose a robust, linear in time modification of Aktouf, Bertrand and Perroton’s algorithm for tunnel (3D hole) closing in 3D volumetric objects. Our algorithm is insensitive to small distortions and branches. The algorithm has been tested on various 3D images including very complicated 3D crack propagation images. The results of the tests, discussion of the algorithm properties and future research plans are also included in the paper.     

IESK-ArDB: a database for handwritten Arabic and an optimized topological segmentation approach

Even though a lot of researches have been conducted in order to solve the problem of unconstrained handwriting recognition, an effective solution is still a serious challenge. In this article, we address two Arabic handwriting recognition-related issues. Firstly, we present IESK-arDB, a new multi-propose off-line Arabic handwritten database. It is publicly available and contains more than 4,000 word images, each equipped with binary version, thinned version as well as a ground truth information stored in separate XML file. Additionally, it contains around 6,000 character images segmented from the database. A letter frequency analysis showed that the database exhibits letter frequencies similar to that of large corpora of digital text, which proof the database usefulness. Secondly, we proposed a multi-phase segmentation approach that starts by detecting and resolving sub-word overlaps, then hypothesizing a large number of segmentation points that are later reduced by a set of heuristic rules. The proposed approach has been successfully tested on IESK-arDB. The results were very promising, indicating the efficiency of the suggested approach.     

Using random walker for knowledge transfer in classifying multi-temporal VHR images

Acquiring land cover types from very high resolution (VHR) images is of great significance to many applications and has been intensively studied for many years. The difficulties in image classification and the high frequencies of remote sensing image acquisition make it urgent to develop efficient knowledge transfer approaches for understanding multi-temporal VHR images. This letter proposed a knowledge transfer approach that uses the label information of the existing VHR images to classify multi-temporal images. The approach was implemented in three steps: object-based change detection, knowledge transfer of label information, and random walker (RW) classification. The proposed approach was tested by two datasets with each having two temporal images acquired on the same geographical areas. The experimental results showed that the proposed approach outperformed the support vector machine (SVM) algorithm in classifying multi-temporal images and can reduce the influence of spectral confusions on image classification.     

基于Euclidean距离的手势识别

提出了一种在距离空间内采用Euclidean距离计算的手势识别算法。手势图像经过边缘检测后,对边缘图像实施Eu-clidean距离变换（EDT）,在距离变换空间内计算距离映射图与样本之间的Euclidean距离。最后,对基于单目视觉的30个手指语字母手势进行识别,最好识别率达93.33%。     

电子邮件系统的研究与实现

在当今Internet时代,电子邮件已经成为人们提供信息交换的必要的通信方式。电子邮件系统通过连接全世界的Internet,实现各类信号的传送、接收、存贮等处理,将邮件送到世界的各个角落,不只局限于信件的传递,还可用来传递文件、声音及图形、图像等不同类型的信息。     

Associative memory design for 256 gray-level images using a multilayer neural network

A design procedure is presented for neural associative memories storing gray-scale images. It is an evolution of a previous work based on the decomposition of the image with 2/sup L/ gray levels into L binary patterns, stored in L uncoupled neural networks. In this letter, an L-layer neural network is proposed with both intralayer and interlayer connections. The connections between different layers introduce interactions among all the neurons, increasing the recall performance with respect to the uncoupled case. In particular, the proposed network can store images with the commonly used number of 256 gray levels instead of 16, as in the previous approach.     

HYLAS: program for generating H curves (abstract three-dimensional representations of long DNA sequences)

The computer program HYLAS generates from a standard DNA letter sequence a three-dimensional space curve (H curve) which embodies the entire information content of the original nucleotide sequence. The program can display H curves either as two-dimensional (front and side view) projections or as stereo-pair images. The curves can be marked at specific nucleotide locations, annotated, rotated for observation from any viewing angle, and manipulated for convenient side-by-side comparisons. Unlike the cumbersome letter sequences, H curves can be drastically condensed in size without losing their ability to reflect the global nucleotide-distribution pattern of the entire DNA sequence. Often, biologically important loci can be visually identified on the H curves. HYLAS is written in FORTRAN with separate mainframe (IBM-VM/CMS) and microcomputer (MS-DOS) versions. It uses the Tektronix-TCS library of graphic subroutines.