Computer Vision, Graphics, and Image Processing最新文献_第7页

Edge contours using multiple scales 使用多个尺度的边缘轮廓

Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90003-E

Donna J Williams, Mubarak Shah

{"title":"Edge contours using multiple scales","authors":"Donna J Williams, Mubarak Shah","doi":"10.1016/0734-189X(90)90003-E","DOIUrl":"10.1016/0734-189X(90)90003-E","url":null,"abstract":"<div><p>An algorithm for finding a single good path through the set of edge points detected by gradient of Gaussian operator is discussed. First, an algorithm for finding contours at one scale is presented, then an extension of that algorithm which uses multiple scales to produce improved detection of weak edges is presented. The set of possible edge points is placed on a priority queue with the edge point having largest magnitude at the top. The strongest edge point that is not already on a contour is retrieved from the queue. The point in the computed direction is examined first, then in those in the adjacent directions on either side of it. Each branch is followed to the end and a weight assigned at each point based on four factors: a measure of noisiness, a measure of curvature, contour length, and the gradient magnitude. The point with the largest average weight is chosen. After searching from the initial point in one direction, a similar search is conducted in the oppositedirection unless a closed contour has been formed. In the algorithm for multiple scales the search for a contour proceeds as for the single scale, using the largest scale, until a best partial contour at that scale has been found. Then the next finer scale is chosen and the neighborhood around the end points of the contour are examined to determine possible edge points in a direction similar to the end point of the contour. The original algorithm is then followed for each of the points satisfying the above condition, and the best is chosen as an extension to the original edge. Further, in order to determine the size neighborhood that should be searched when attempting to pick up an edge at a smaller scale, a theoretical analysis of the movement of idealized edges is performed. This analysis examines two adjacent step edges having the same parity (a staircase) and opposite parity (a pulse). It is determined that maximum movement for both cases is σ, where σ is the standard deviation of the Gaussian used. This maximum movement occurs for the staircase when the two nearby edges have the same step size and are at a distance of 2σ apart. However, for edges closer or farther away, maximum movement decreases rapidly. For a pulse, maximum movement occurs when the two edges have the same step size and are very close together. Again the movement decreases rapidly as the edges become farther apart. Movement also decreases in both cases when the relative strengths of the two edges are not equal.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Pages 256-274"},"PeriodicalIF":0.0,"publicationDate":"1990-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0734-189X(90)90003-E","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126231537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 69

A semi-analytic method of determining stereo camera geometry from matched points in a pair of images: Coincident meridional planes, exact or noisy data 从一对图像中的匹配点确定立体摄像机几何形状的半解析方法:重合的子午面，精确或有噪声的数据

Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90005-G

Harit P Trivedi

{"title":"A semi-analytic method of determining stereo camera geometry from matched points in a pair of images: Coincident meridional planes, exact or noisy data","authors":"Harit P Trivedi","doi":"10.1016/0734-189X(90)90005-G","DOIUrl":"10.1016/0734-189X(90)90005-G","url":null,"abstract":"<div><p>We describe a novel semi-analytic method to determine the parameters of stereo camera geometry from pairs of matched points under the restriction of coincident meridional lanes. By a judicious choice of variables to represent rotation and translation, the noise-free problem reduces to solving two quadratics—one in each variable. With noissy data, the least squares problem reduces to a fifth-degree polynomial in a single variable, all the solutions of which can be (numerically) exactly computed along with an estimate of the standard deviation. The problem of locating the global minimum of the error function in two variables (which generally admits an unpredictable number of local extrema) in this instance becomes that of comparing five numbers. <em>The global minimum can therefore be guaranteed</em>. The algorithm does not break down whether or not the translation vanishes. In fact, we propose an effective signature to detect vanishing translation in the presence of noise. The general algorithm also handles the degenerate case of all imaged points lying in a vertical plane which is known to admit two solutions. Both solutions are found.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Pages 299-312"},"PeriodicalIF":0.0,"publicationDate":"1990-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0734-189X(90)90005-G","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125318856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Author index for volume 51 第51卷作者索引

Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90015-N

引用次数: 0

Three-frame corner matching and moving object extraction in a sequence of images 序列图像中三帧角匹配与运动目标提取

Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90010-S

Hsi-Jian Lee

引用次数: 0

A color clustering technique for image segmentation 一种用于图像分割的颜色聚类技术

Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90009-K

Mehmet Celenk

引用次数: 0

Template quadtrees for representing region and line data present in binary images 模板四叉树表示区域和线数据存在于二值图像

Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90007-I

M Manohar , P.Sudarsana Rao, S.Sitarama Iyengar

{"title":"Template quadtrees for representing region and line data present in binary images","authors":"M Manohar , P.Sudarsana Rao, S.Sitarama Iyengar","doi":"10.1016/0734-189X(90)90007-I","DOIUrl":"10.1016/0734-189X(90)90007-I","url":null,"abstract":"<div><p>A template-based quadtree data structure for representing image features like regions and lines is described. This data structure called template quadtree (TQT) stores the region and line data present in a binary image in the leaf nodes if they correspond to one of the predetermined templates; otherwise it is quadrantized. This is recursively performed until the entire image is reduced to templates of different sizes in leaf nodes at different levels. The template size is 2<sup><em>k</em></sup> × 2<sup><em>k</em></sup>, where <em>k</em> is an integer greater than 0. The different types of templates considered are uniform color (black and white) horizontal, vertical, and diagonal lines. The number of templates possible for a given subimage of size 2<sup><em>k</em></sup> × 2<sup><em>k</em></sup> is 6 × 2<sup><em>k</em></sup>. The region quadtree is a special case of the TQT is which the template corresponds to uniform color (black and white). Since the least size template is 2 × 2 the storage requirement of TQT is about four times less in the worst case situation like checkerboard. The representation of lines is based on pixels rather than storing lines that are fitted to the array of pixels. Thus this representation is accurate and reconstruction procedures are straightforward. The main feature of this representation scheme are: (i) it is capable of representing both region and line data; and (ii) it does not involve approximations. This paper describes TQT data structure, construction of TQTs from the binary images, and reconstruction. A brief description of some of the common operations on images using TQT data structure is given.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Pages 338-354"},"PeriodicalIF":0.0,"publicationDate":"1990-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0734-189X(90)90007-I","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129917883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Object detection by step-wise analysis of spectral, spatial, and topographic features 通过逐步分析光谱、空间和地形特征的目标检测

Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90002-D

Mohan M Trivedi, ChuXin Chen, Daniel H Cress

{"title":"Object detection by step-wise analysis of spectral, spatial, and topographic features","authors":"Mohan M Trivedi, ChuXin Chen, Daniel H Cress","doi":"10.1016/0734-189X(90)90002-D","DOIUrl":"10.1016/0734-189X(90)90002-D","url":null,"abstract":"<div><p>In many computer vision systems accurate identification of various objects appearing in a scene is required. In this paper we address the problem of object detection in analyzing high resolution multispectral aerial images. Development of a practical object detection approach should consider issues of speed, accuracy, robustness, and amount of supervision allowed. The approach is based upon extraction of information from images and their systematic analysis utilizing available prior knowledge of various physical attributes of the objects. The step-wise approach examines spectral, spatial, and topographic features in making the object vs background decision. Techniques for the analysis of the spectral, spatial, and topographic features tend to be of increasing levels of computational complexity. The computationally simpler spectral feature analysis is performed for the entire image to detect candidate object regions. Only these regions are considered in the spatial feature analysis step to further reduce the number of candidate regions which need to be analyzed in the topographic feature analysis step. Such step-wise analysis makes the entire object detection process efficient by incorporating the process of “focus of attention” to identify regions of interest thus eliminating a relatively large portion of image from further detailed examination at every stage. Results of the experiments performed using several high resolution multispectral images have demonstrated the basic feasibility of the approach. The images utilized in the experiments are acquired from geographically different locations, at different times, with different types of background, and are of different resolution. Successful object detection with high accuracy and low false alarm rates indicate the robustness of this approach.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Pages 235-255"},"PeriodicalIF":0.0,"publicationDate":"1990-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0734-189X(90)90002-D","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128883637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Detecting runways in complex airport scenes 在复杂的机场场景中探测跑道

Computer Vision, Graphics, and Image Processing Pub Date : 1990-08-01 DOI: 10.1016/0734-189X(90)90027-S

A. Huertas, W. Cole, R. Nevatia

引用次数: 70

A hierarchical approach to line extraction based on the hough transform 基于霍夫变换的分层线提取方法

Computer Vision, Graphics, and Image Processing Pub Date : 1990-08-01 DOI: 10.1016/0734-189X(90)90033-R

John Princen, John Illingworth, Josef Kittler

引用次数: 0

A structure feature for some image processing applications based on spiral functions 一些基于螺旋函数的图像处理应用的结构特征

Computer Vision, Graphics, and Image Processing Pub Date : 1990-08-01 DOI: 10.1016/0734-189X(90)90029-U

Josef Bigu¨n

{"title":"A structure feature for some image processing applications based on spiral functions","authors":"Josef Bigu¨n","doi":"10.1016/0734-189X(90)90029-U","DOIUrl":"10.1016/0734-189X(90)90029-U","url":null,"abstract":"<div><p>A new low-level vision primitive based on logarithmic spirals is presented for various image processing tasks. The detection of such primitives is equivalent to detection of lines and edges in another coordinate system which has been used to model the mapping of the visual field to the striate cortex. Algorithms detecting the proposed primitives and pointing out a matched subclass are presented along with necessary theory. As a result, if the local structure is describable by the proposed primitives then a certainty parameter based on a well-defined mismatch (error) function will indicate this. Moreover, the best fit of a subclass of the proposed primitives in the least squares sense will be computed. The resulting images are unthresholded. They are computed by means of simple convolutions and pixelwise arithmetic operations which make the algorithms suitable for real time image processing applications. Since the resulting images contain information about the local structure, they can be used as feature images in applications like remote sensing, texture analysis, and object recognition. Experimental results on the latter including synthetic as well as natural images are presented along with noise sensitivity tests. The results exhibit good detection properties for the subclasses of the modelled primitives along with uniform and reliable behavior of the corresponding certainty measures.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 2","pages":"Pages 166-194"},"PeriodicalIF":0.0,"publicationDate":"1990-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0734-189X(90)90029-U","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74962461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18