Detect the intersect lines of multiple planes is one way to recognize and reconstruct the 3D space. First, analyzed the depth data grabbed by SR3000, sampled the depth data into gray bitmap and detect the depth gradient edge. By using the improved Hough Transformation method, get the parameters of spatial intersection lines.

Super resolution image reconstruction is a new technology which means to use multiple video sequences,or single-frame image and the training sample images of complementary information between the images to reconstruct a better quality,higher spatial resolution image data,make up the original image data is the lack of spatial resolution,improved image spatial resolution for force and clarity.Describes the method based on regularization of the super-resolution image reconstruction.On this basis,using the L1 norm of the reconstructed image fidelity constraint,the use of total variation regularization to overcome the ill-conditioned reconstruction problems,effectively maintain the edge of the image.To achieve a text message containing the image of regularized super-resolution reconstruction,experimental verification of the effectiveness of the method.

Remote sensing technology arised in the 1960s and developed into a comprehensive detection technology,while remote sensing technology has been used in many fields widely.the face massive remote sensing image data,the quality and efficiency of interpretation is important.Based on summarizing the main difficulties and deficiencies of remote sensing information extraction technology in the past,the paper focuses on urban features of remote sensing information extraction technology ideas about object-oriented,the finally,summarfized and analyzed this idea,pointing out that the current problems and future research directions.

An averaging filtering algorithm was proposed based on the analysis of classical median and aneraging filter algorithm,and the principles and implementing steps were given.Comparison experiments between it and the classical averaging filter algorithm.The experimental results indicated the excellent filtering performance and accelerating calculating speed from subjective impression and objective parameters.

The Gabor motion energy filter(GME) is applied to dynamic facial expressions.Finally,comparative experiments are carried out in the Cohn-Kanade face database.They show that GME outperforms GE on low intensity expression discrimination.

An efficient algorithm was presented for the statistics of traffic flows including that illumination was not sufficient at night.Firstly,In order to separate the foreground from background,the original video sequences had been thresholded,and by using morphological erosion to eliminate some isolated noises and smaller regions,these regions whose ranges are smaller than the one enacted were discarded by looking for connective regions,and the beams which were projected by headlamps and detached,were connected by the morphological expansion.Secondly,calculating and judging the areas and ranges of connective regions to extract accurately the headlights.Finally,comparing the headlights' areas and position of two adjacent frames to match and track,then calculate traffic flows.Experiment results indicate that this algorithm is low about computation,and its detection ratio reaches above 97% in fine condition.

Camshift is a tracking algorithm based on color histogram.It operates on a back-projection image produced from object histogram model.Initialize a search window size and location.Computer information is used previously to adjust current search window size and location,then location center of the object in the current image.The tracking speed is raised by virtue of predicting the position that a moving object arrives at the next time and reducing the search region.The experimental results are given to show that the proposed algorithm can improve object tracking speed even if complex background and irregular motion.

In allusion to describe detection and tracking of moving targets, it is an import role of the appearance of optical flow, especially for real-time detection of vehicle under dynamic background. There are many advantages for optical flow than other means. The key idea in this paper is to introduce detection both under static and dynamic background. Optical Flow is a more complex algorithm than others because of its large calculation. So in this paper choose to extract features to assist optical flow algorithm in order to lessen work. At the same time, to collect ROI at the basis of some prepro- cessing play a very important part to detect under dynamic background. After these steps we can obtain rough optical flow, so we should make template matching to cut out noise which we don＇t like. So we can get nice result at the end.

The paper introduces how to extract the human star skeleton and by using the particle swarm to optimize the skeleton characteristic vector quantization.Star skeleton,generated by connecting human center-of-mass point to the human limbs and head endpoint,is a kind of fast skeleton extraction techniques.Connecting center-of-mass point with endpoint,human skeleton could be represented by five dimensional vector Si,Si∈Rn,Rn is the star skeleton feature space.Star skeleton sequence can take the place of the timing sequences of human actions.Finally,we generated the codebook G by using particle swarm optimization quantification process.

Frames difference to get moving regions,gradient threshold to get binary images.extracting feature points'optical flow of moving regions,marking optical flow vector by section,setting up ROI,using optical flow to get identification,orientation,tracking of moving target are introduced.This method has real-time and robustness to moving target tracking.It can be used in traffic flow statistics and is also a bedding of driver assistance research.Experimental results show the effectiveness and practical of this method.

In a series of image frames of the moving object to the template method as a model for histogram matching, due to a very large amount of template matching. It is not possible to target the whole image, but also meet the real-time search and matching .If we aim to conduct a reliable estimate, it can be completed in a relatively small region of the search template. Kalman filter is a linear sequence of the dynamic systems, the state minimum variance estimation algorithm. Through dynamic equations to describe the equation of state and observation systems, it can arbitrarily observe point as a starting point, and recursive filtering method. It is a small amount with the characteristics of real-time computation.

As an important part of the technology for human-machine interface, facial expression recognition have drawn much attention recently. In this paper, we present an effective method ,which uses the discrete cosine transform (DCT) and back propagation (BP) neutral network . First ,processing including normalization and filtering is carried out on facial images .Then discrete cosine transform is introduced. At last, recognition is made based on the back propagation neutral network.

Based on image contextual regions and overlap,an enhancement method for non-umiformly illuminated image is presented in this paper.According to regional characteristics,power and other mapping functions are adopted adaptively,redistributing the region's histogram.Then bilinear interpolation will avoid un-smooth transition among contextual regions.Compared with the traditional method,this method can enhance non-uniformly illuminated image clearly with faster speed and less background noise.

With the rapid development of computer science,image process and pattern recognition technologies,people are paying more and more attention on parallel two-eyes-visual system and three-dimension reconstruction.The research has applied in many fields.We study and design a set of two-eyes-visual system to obtain pictures vividly.Cubic-image-depth-map based on two-eye vision technology is the key technique for reconstructing 3D-shapes out of 2D-images.So the quality of depth-map can directly influence the result of three-dimensional-image reconstruction.The depth-map has gained more and more attentions in the field of computer vision.

一、概述 昆明市公安局在昆明市主城建成区周边12个主要出城路口建设了含车牌照自动识别的公路车辆智能监测记录系统,同时在公交分局指挥中心建设中心管理系统.从而实现了对通过各个卡口的机动车辆进行实时车辆图像采集,自动牌照识别,对嫌疑车辆与被盗枪机动车数据库比对报警,存储记录,联网布防的治安科技防控功能.

A new method for objective assessing image quality is presented.This method is based on gradient magnitude. and does not need the original image for reference. It is suitable for comparing two or more same images which have different qualities. Experimental results show that the proposed scheme is effective. It is in accordance with the conventional subjective method in most of the cases, and is easily implemented.

车牌照是全世界唯一对车辆身份识别的标记.尽管牌照的字符、颜色、格式内容和制作材料会多种多样,但车牌照仍是全球范围内最为精确和特定的识别标记.根据国际交通技术有关统计,全世界范围内除中国以外,已经有78家公司在生产车牌识别产品.

目前,在高速公路收费管理中车牌识别技术的应用面越来越广,并且产品形式各异,包括软件嵌入式、软硬件一体式等.本文分析嵌入式车牌识别软件在高速公路收费系统中的应用.

根据特征脸思想,提出了一种新的基于特征肤色的人脸检测方法.首先从RGB彩色空间转换到HSI彩色空间中,然后训练肤色点样本集得到特征肤色,最后在特征肤色构成的肤色空间中检测人脸.实验表明,该方法是快速的、鲁棒的.

A fast algorithm for the restoration of an image is presented.The image is described by using chain codes which record the contours of the image.The contour of an image is traced and smoothed according to chain codes description,from which the chain code is given.then a simple idea for region filling is proposed in our algorithm.