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Systolic implementation of the adaptive solution to normal equations 实现了收缩正常方程的自适应解
Computer Vision, Graphics, and Image Processing Pub Date : 1990-10-01 DOI: 10.1016/0734-189X(90)90132-F
P. Common, Y. Robert, D. Trystram
{"title":"Systolic implementation of the adaptive solution to normal equations","authors":"P. Common, Y. Robert, D. Trystram","doi":"10.1016/0734-189X(90)90132-F","DOIUrl":"https://doi.org/10.1016/0734-189X(90)90132-F","url":null,"abstract":"","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"52 1","pages":"Page 144"},"PeriodicalIF":0.0,"publicationDate":"1990-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0734-189X(90)90132-F","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136556980","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: 0
Using feature probabilities to reduce the expected computational cost of template matching 利用特征概率降低模板匹配的预期计算成本
Computer Vision, Graphics, and Image Processing Pub Date : 1990-10-01 DOI: 10.1016/0734-189X(90)90125-F
Avraham Margalit, Azriel Rosenfeld
{"title":"Using feature probabilities to reduce the expected computational cost of template matching","authors":"Avraham Margalit,&nbsp;Azriel Rosenfeld","doi":"10.1016/0734-189X(90)90125-F","DOIUrl":"10.1016/0734-189X(90)90125-F","url":null,"abstract":"<div><p>Matching of two digital images is computationally expensive, because it requires a pixel-by-pixel comparison of the pixels in the image and in the template for every location in the image. In this paper we present a technique to reduce the computational cost of template matching by using probabilistic knowledge about local features that appear in the image and the template. Using this technique the most probable locations for successful matching can be found. In the paper we discuss how the size of the features affects the computational cost and the robustness of the technique. We also present results of experiments showing that even simple methods of feature extraction and representation can reduce the computational cost bymmore than an order of magnitude.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"52 1","pages":"Pages 110-123"},"PeriodicalIF":0.0,"publicationDate":"1990-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0734-189X(90)90125-F","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128872531","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: 12
Using probabilistic domain knowledge to reduce the expected computational cost of template matching 利用概率领域知识降低模板匹配的预期计算量
Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90001-C
Avraham Margalit, Azriel Rosenfeld
{"title":"Using probabilistic domain knowledge to reduce the expected computational cost of template matching","authors":"Avraham Margalit,&nbsp;Azriel Rosenfeld","doi":"10.1016/0734-189X(90)90001-C","DOIUrl":"10.1016/0734-189X(90)90001-C","url":null,"abstract":"<div><p>Matching of two digital images is computationally expensive, because it requires a pixel-by-pixel comparison of the pixels in the image and in the template. If we have probabilistic models for the classes of images being matched, we can reduce the expected computational cost of matching by comparing the pixels in an appropriate order. In this paper we show that the expected cumulative error when matching an image and a template is maximized by using an ordering technique. We also present experimental results for digital images, when we know the probability densities of their gray levels, or more generally, the probability densities of arrays of local property values derived from the images.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Pages 219-234"},"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)90001-C","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122280604","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: 21
The arc tree: An approximation scheme to represent arbitrary curved shapes 弧树:表示任意曲线形状的近似方案
Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90006-H
Oliver Günther, Eugene Wong
{"title":"The arc tree: An approximation scheme to represent arbitrary curved shapes","authors":"Oliver Günther,&nbsp;Eugene Wong","doi":"10.1016/0734-189X(90)90006-H","DOIUrl":"https://doi.org/10.1016/0734-189X(90)90006-H","url":null,"abstract":"<div><p>This paper introduces the <em>arc tree</em>, a hierarchical data structure to represent arbitrary curved shapes. The arc tree is a balanced binary tree that represents a curve of length <em>l</em> such that any subtree whose root is on the <em>k</em>th tree level is representing a subcurve of length <span><math><mtext>l</mtext><mtext>2</mtext><msup><mi></mi><mn>k</mn></msup></math></span>. Each tree level is associated with an approximation of the curve; lower levels correspond to approximations of higher resolution. Based on this hierarchy of detail, queries such as point search or intersection detection and computation can be solved in a hierarchical manner. Algorithms start out near the root of the tree and try to solve the queries at a very coarse resolution. If that is not possible, the resolution is increased where necessary. We describe and analyze several such algorithms to compute a variety of set and search operators. Various related approximation schemes to represent curved shapes are also discussed.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Pages 313-337"},"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)90006-H","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"137435597","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: 0
Refining edges detected by a LoG operator 细化由LoG操作符检测到的边缘
Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90004-F
Fatih Ulupinar, Gérard Medioni
{"title":"Refining edges detected by a LoG operator","authors":"Fatih Ulupinar,&nbsp;Gérard Medioni","doi":"10.1016/0734-189X(90)90004-F","DOIUrl":"https://doi.org/10.1016/0734-189X(90)90004-F","url":null,"abstract":"<div><p>The Laplacian-of-Gaussian (LoG) operator is one of the most popular operators used in edge detection. This operator, however, has some problems: zero-crossings do not always correspond to edges, and edges with an asymmetric profile introduce a symmetric bias between edge and zero-crossing locations. In this paper, we offer solutions to these two problems. First, for one-dimensional signals, such as slices from images, we propose a simple test to detect “true” edges, and, for the problem of bias, we propose different techniques: the first one combines the results of the convultion of two LoG operators of different standard deviations, whereas the others sample the convolution with a single LoG filter at two points besides the zero-crossing. In addition to localization, these methods allow us to further characterize the <em>shape</em> of the edge. We then present an implementation of these techniques for edges in 2D images, in which we apply the refining process to linear segments approximating the detected contours. The methods are illustrated on several examples.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Pages 275-298"},"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)90004-F","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"137435619","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: 0
Boundary and object labelling in three-dimensional images 三维图像中的边界和目标标记
Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90008-J
Jayaram K Udupa, Venkatramana G Ajjanagadde
{"title":"Boundary and object labelling in three-dimensional images","authors":"Jayaram K Udupa,&nbsp;Venkatramana G Ajjanagadde","doi":"10.1016/0734-189X(90)90008-J","DOIUrl":"10.1016/0734-189X(90)90008-J","url":null,"abstract":"<div><p>There are many imaging modalities (e.g., medical imaging scanners) that capture information about internal structures and generate three-dimensional (3D) digital images of the distribution of some physical property of the material of the structure. Such images have been found to be very useful in analyzing the form and function of the structure and in detecting and correcting deformities in the structure. Visualization of 3D structures is an essential component of such analyses. One commonly used approach to visualization consists of identifying the structure of interest, forming its surfaces, and then rendering the surfaces on a two-dimensional screen. This paper addresses the surface formation problem assuming that object identification has already been done and a 3D binary image is available that represents the structure. For the existing 3D boundary tracking algorithms, the user has to somehow specify each surface that is to be tracked. Often, the 3D image consists of many surfaces of interest. Their manual specification is very tedious and may be impossible if the structure is of complex shape. This paper describes a methodology for automatically tracking all boundary surfaces—i.e., labelling boundary surfaces—in the given 3D image. The algorithms also generate additional information from which the 3D connected components in the image are trivially obtained. Examples from medical imaging are included to illustrate the usefulness of the new methodology.</p></div>","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Pages 355-369"},"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)90008-J","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123854471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 57
Shape from texture using the Wigner distribution 形状从纹理使用维格纳分布
Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90013-L
Jack Y Jau, Roland T Chin
{"title":"Shape from texture using the Wigner distribution","authors":"Jack Y Jau,&nbsp;Roland T Chin","doi":"10.1016/0734-189X(90)90013-L","DOIUrl":"https://doi.org/10.1016/0734-189X(90)90013-L","url":null,"abstract":"","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Page 371"},"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)90013-L","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136547447","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: 0
Finding point correspondences and determining motion of a rigid object from two weak perspective views 从两个弱透视视图中寻找点对应并确定刚性物体的运动
Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90014-M
Chia-Hoang Lee, Thomas Huang
{"title":"Finding point correspondences and determining motion of a rigid object from two weak perspective views","authors":"Chia-Hoang Lee,&nbsp;Thomas Huang","doi":"10.1016/0734-189X(90)90014-M","DOIUrl":"https://doi.org/10.1016/0734-189X(90)90014-M","url":null,"abstract":"","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Page 371"},"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)90014-M","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136547516","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: 0
Parallel shrinking algorithms using 2-subfield approaches 使用2-子域方法的并行收缩算法
Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90011-J
Muhittin Gökmen, Richard W Hall
{"title":"Parallel shrinking algorithms using 2-subfield approaches","authors":"Muhittin Gökmen,&nbsp;Richard W Hall","doi":"10.1016/0734-189X(90)90011-J","DOIUrl":"10.1016/0734-189X(90)90011-J","url":null,"abstract":"","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Page 370"},"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)90011-J","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76584357","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: 3
Polygonal representation: A maximum likelihood approach 多边形表示:最大似然方法
Computer Vision, Graphics, and Image Processing Pub Date : 1990-09-01 DOI: 10.1016/0734-189X(90)90012-K
Thomas L Hemminger, Carlos A Pomalaza-Ráez
{"title":"Polygonal representation: A maximum likelihood approach","authors":"Thomas L Hemminger,&nbsp;Carlos A Pomalaza-Ráez","doi":"10.1016/0734-189X(90)90012-K","DOIUrl":"https://doi.org/10.1016/0734-189X(90)90012-K","url":null,"abstract":"","PeriodicalId":100319,"journal":{"name":"Computer Vision, Graphics, and Image Processing","volume":"51 3","pages":"Pages 370-371"},"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)90012-K","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136547446","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: 0
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