Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation最新文献

Image classification in remote sensing using functional link neural networks 基于功能链接神经网络的遥感图像分类

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation Pub Date : 1994-04-21 DOI: 10.1109/IAI.1994.336685

L.M. Liu, M. Manry, F. Amar, M. Dawson, A. Fung

引用次数: 22

Frequency domain measurement of meteorological range from aircraft images 从飞机图像测量气象距离的频域

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation Pub Date : 1994-04-21 DOI: 10.1109/IAI.1994.336684

J. Barrios, D. Williams, J. Cogan, J. Smith

引用次数: 3

Artificially intelligent 3D industrial inspection system for metal inspection 用于金属检测的人工智能三维工业检测系统

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation Pub Date : 1994-04-21 DOI: 10.1109/IAI.1994.336670

S. Panayiotou, A. Soper

引用次数: 3

An algorithm for 3D scene description in an unknown environment 未知环境下的三维场景描述算法

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation Pub Date : 1994-04-21 DOI: 10.1109/IAI.1994.336669

Y. Dong, T. Chen, L. Sheppard

{"title":"An algorithm for 3D scene description in an unknown environment","authors":"Y. Dong, T. Chen, L. Sheppard","doi":"10.1109/IAI.1994.336669","DOIUrl":"https://doi.org/10.1109/IAI.1994.336669","url":null,"abstract":"Scene description plays a major role in the interpretation of images. In the paper a novel data- and rule-driven system for 3D segmentation and scene description in an unknown environment is presented. This system generates hierarchies of features that correspond to structural elements such as boundaries and shape classes of individual objects as well as relationships between objects. It is implemented as an added high-level component to an existing low-level binocular vision system (Don and He, 1988). Based on a pair of matched stereo images produced by that system, 3D segmentation is first performed to group object boundary data into several edge-sets each of which is believed to belong to one particular object. Then gross features of each object are extracted and stored in an object record. The final structural description of the scene is accomplished with information in the object record, a set of rules and a rule implementor. The system is designed to handle partially occluded objects of different shape and size on the 2D images. Experimental results have shown its success in computing both object and structural level descriptions of common man-made objects.<<ETX>>","PeriodicalId":438137,"journal":{"name":"Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115380852","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

Parameter estimation and applications of a class of Gaussian image models 一类高斯图像模型的参数估计及其应用

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation Pub Date : 1994-04-21 DOI: 10.1109/IAI.1994.336689

G. Dattatreya, Xiaori Fang

引用次数: 0

Radar imaging using 2D adaptive non-parametric extrapolation and autoregressive modeling 雷达成像采用二维自适应非参数外推和自回归建模

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation Pub Date : 1994-04-21 DOI: 10.1109/IAI.1994.336682

C. Chen, G. Thomas, B. Flores, S. Cabrera

引用次数: 0

An image segmentation technique based on edge-preserving smoothing filter and anisotropic diffusion 基于边缘保持平滑滤波和各向异性扩散的图像分割技术

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation Pub Date : 1994-04-21 DOI: 10.1109/IAI.1994.336683

T. Dang, O. Jamet, H. Maître

引用次数: 5

Recognition of 3-D objects on complex backgrounds using model based vision and range images 利用基于模型的视觉和距离图像识别复杂背景下的三维物体

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation Pub Date : 1994-04-21 DOI: 10.1109/IAI.1994.336667

E. Natonek, C. Baur

{"title":"Recognition of 3-D objects on complex backgrounds using model based vision and range images","authors":"E. Natonek, C. Baur","doi":"10.1109/IAI.1994.336667","DOIUrl":"https://doi.org/10.1109/IAI.1994.336667","url":null,"abstract":"One of the active research fields in computer vision is the recognition of complex 3D objects. The task of object recognition is tightly bound to background understanding or suppression. Current literature describes the top down approaches as promising but not complete and the bottom-up approaches as not robust. The paper describes a model based vision system in which a commercial 3D computer graphics system has been used for object modeling and visual clue generation. Given the computer generated model image, a conventional CCD camera image and the corresponding scanned 3D dense range map of the real scene, the object can be located in it. The paper deals with how this is done using newly developed segmentation algorithms extracting \"focus features\" from range images (depth map) of the scene. The system uses the image pyramid of resolution and prediction-verification process. First the authors generate a hypothesis in a low resolution description, giving rough clues for the object boundaries, position and orientation. These regions of interest are then used as the field of comparison with higher resolution models. Such an iterative process is repeated until a given threshold of similarity is reached. Next an intensity image of the model in the scene is created using the available a priori knowledge. Direct correlation is then performed between the model and the \"focus feature\" of the scene. Illustrative examples of object recognition in simple and complex scenes are presented.<<ETX>>","PeriodicalId":438137,"journal":{"name":"Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129554821","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: 1

Sensitivity analysis of similarity metrices for image matching 图像匹配相似性度量的灵敏度分析

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation Pub Date : 1994-04-21 DOI: 10.1109/IAI.1994.336681

R. Malla, V. Devarajan

引用次数: 2

Application of spatial grey level dependence methods to digitized mammograms 空间灰度相关性方法在数字化乳房x线照片中的应用

Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation Pub Date : 1994-04-21 DOI: 10.1109/IAI.1994.336675

B. Aldrich, M. Desai

{"title":"Application of spatial grey level dependence methods to digitized mammograms","authors":"B. Aldrich, M. Desai","doi":"10.1109/IAI.1994.336675","DOIUrl":"https://doi.org/10.1109/IAI.1994.336675","url":null,"abstract":"The efficacy of using spatial grey level dependence (SGLD) methods is proposed for the evaluation of the textural content of digitized mammograms. In film-screen mammography, the physician uses his awareness of features present on the mammogram to achieve the diagnosis of (or absence of) a disease state. The image perceived by the physician represents the projection of a 3D object onto film and certain limitations are imposed by the characteristics of the imaging modality as well as by the means for creating a discrete representation of the image. Spatial grey level dependence methods have the promise to reveal significant salient information about the underlying structural elements that indicate disease and also have the potential to provide additional information with regard to the medical objective. In the paper, statistics computed from the SGLD are used to highlight features of potential medical interest in mammograms. In particular, the local energy and inertia are calculated for malignant and benign lesions. In preliminary results, it is found that these measurements have an apparent ability to provide discrimination between regions of low textural energy and randomness from regions of high textural energy and randomness. Typically, these types of regions are associated with benign and malignant image profiles, respectively. Examples are given where these techniques are applied to lesions in digitized mammograms at a 100 micron spatial resolution and 12 bit gray scale resolution.<<ETX>>","PeriodicalId":438137,"journal":{"name":"Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127308708","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: 16