A description is given of a knowledge-based vision system for recognizing and classifying man-made objects in aerial images. images are interpreted and image object descriptors are created, based on model-driven high-...
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ISBN:
(纸本)0818608625
A description is given of a knowledge-based vision system for recognizing and classifying man-made objects in aerial images. images are interpreted and image object descriptors are created, based on model-driven high-level vision processing. Knowledge of various low-level vision techniques, and their applicability to generic applications are used to dynamically select specific low-level vision techniques for image segmentation. Terrain map and feature information is used as an adjunct by the low-level vision to assist in image segmentation, and by high-level vision for image interpretation. The authors have used a unique software architecture based on standard knowledge-based approaches in which knowledge is represented explicitly and is separated from program control. Off-the-shelf tools including Lisp and the ART language from Inference corporation, running on a Symbolics 3675, were used. The current system has been tested both with low-resolution forward-looking infrared (FLIR) images for target cueing and higher-resolution airport scenes for scene analysis.
A high level imageprocessing.language is discussed that provides a robust environment for the universal specification and implementation of imageprocessing.algorithms. In essence, an imageprocessing.program consist...
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ISBN:
(纸本)0818608625
A high level imageprocessing.language is discussed that provides a robust environment for the universal specification and implementation of imageprocessing.algorithms. In essence, an imageprocessing.program consists of a collection of procedure calls. To implement an algorithm, one need only construct a block-diagram representation of the algorithm and then proceed with the one-to-one translation of the block diagram into the host PASCAL language. The result is that an investigator can proceed with rapid variations at the algorithm design stage without having to be involved with writing code. The development of the language rests on three pillars: (1) the existence of a rigorous and robust image algebra, (2) the block diagram specification of image-processing.algorithms, and (3) the bound matrix image representation.
An efficient mapping frame a tree structure into a pipelined array of 2log N stages is presented for processing.an N × N image. In the proposed mapping structure, the identification of the information growing pro...
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ISBN:
(纸本)0818608625
An efficient mapping frame a tree structure into a pipelined array of 2log N stages is presented for processing.an N × N image. In the proposed mapping structure, the identification of the information growing property inherent in feature-extraction algorithms allows bit-level concurrency to be exploited in the architectural design. Accordingly, the design of each staged pipelined processor is simplified.
The author discusses some of the properties of vertex space, including insensitivity to changes in scale, orientation, and partial object occlusion, and how these properties relate to problems in model-based object re...
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ISBN:
(纸本)0818608625
The author discusses some of the properties of vertex space, including insensitivity to changes in scale, orientation, and partial object occlusion, and how these properties relate to problems in model-based object recognition. He also describes techniques developed for 2-D and 3-D object recognition using vertex space. The vertex-space approach to object recognition is powerful and efficient, deals well with missing information, and does not require conventional region segmentation. Results to date and an indication of future research directions are presented.
The authors present a method that combines region growing and edge detection for image segmentation. They start with a split-and-merge algorithm where the parameters have been set up so that an oversegmented image res...
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ISBN:
(纸本)0818608625
The authors present a method that combines region growing and edge detection for image segmentation. They start with a split-and-merge algorithm where the parameters have been set up so that an oversegmented image results. Then region boundaries are eliminated or modified on the basis of criteria that integrate contrast with boundary smoothness, variation of the image gradient along the boundary, and a criterion that penalizes for the presence of artifacts reflecting the data structure used during segmentation (quadtree, in this case).
Given a sequence of images taken from a moving camera, they are registered with subpixel accuracy in respect to translation and rotation. The subpixel registration allows image ehancement with respect to improved reso...
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ISBN:
(纸本)0818608625
Given a sequence of images taken from a moving camera, they are registered with subpixel accuracy in respect to translation and rotation. The subpixel registration allows image ehancement with respect to improved resolution and noise cleaning. Both the registration and the enhancement procedures are described. The methods are particularly useful for image sequences taken from an aircraft or satellite where images in a sequence differ mostly by translation and rotation. In these cases, the process results in images that are stable, clean, and sharp.
A weak structural texture analysis technique for determining wave heights from images is presented. Based on the representation of ocean waveforms by relational trees, the absolute peak heights, the relative peak heig...
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ISBN:
(纸本)0818608625
A weak structural texture analysis technique for determining wave heights from images is presented. Based on the representation of ocean waveforms by relational trees, the absolute peak heights, the relative peak heights, and the peak width are extracted. The histogram of peak heights for a given width is obtained, and a weak structural texture measure is constructed to discriminate the different ocean-wave heights.
Various types of moments have been used to recognize imagepatterns in a number of applications. The authors evaluate a number of moments and address some fundamental questions, such as image representation ability, n...
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ISBN:
(纸本)0818608625
Various types of moments have been used to recognize imagepatterns in a number of applications. The authors evaluate a number of moments and address some fundamental questions, such as image representation ability, noise sensitivity, and information redundancy. Moments considered here include regular moments, Legendre moments, Zernike moments, pseudo-Zernike moments, rotational moments and complex moments. Properties of these moments are examined in detail, and the interrelationships among them are discussed. Both theoretical and experimental results are presented.
A method is presented for depth recovery through the analysis of scene sharpness across changing focus position. Modeling a defocused image as the application of a low pass-filter on a properly focused image of the sa...
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ISBN:
(纸本)0818608625
A method is presented for depth recovery through the analysis of scene sharpness across changing focus position. Modeling a defocused image as the application of a low pass-filter on a properly focused image of the same scene, the authors can compare the high spatial frequency content of regions in each image and determine the correct focus position. Recovering depth in this manner is inherently a local operation, and can be done efficiently using a pipelined image processor. Laplacian and Gaussian pyramids are used to calculate maps which are collected and compared to find the focus position that maximizes high spatial frequencies for each region.
A uniform hierarchical procedure for processing.incomplete image data is described. It begins with the computation of local moments within windows centered on each output sample point. Arrays of such measures, called ...
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ISBN:
(纸本)0818608625
A uniform hierarchical procedure for processing.incomplete image data is described. It begins with the computation of local moments within windows centered on each output sample point. Arrays of such measures, called moment images, are computed efficiently through the application of a series of small kernel filters. A polynomial surface is then fit to the available image data within a local neighborhood of each sample point. Best-fit polynomials are obtained from the corresponding local moments. The procedure, hierarchical polynomial fit filtering, yields a multiresolution set of low-pass-filtered images. The set of low-pass images is combined by multiresolution interpolation to form a smooth surface passing through the original image data.
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