This paper presents an automatic method for processing digitized images of cadastral maps. The method includes two major algorithms: a segmentation and a Raster-to-Vector conversion. Those algorithms use a simple data...
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This paper presents an automatic method for processing digitized images of cadastral maps. The method includes two major algorithms: a segmentation and a Raster-to-Vector conversion. Those algorithms use a simple data-list structure for recording data created during single-pass, row-majority scanning and line tracing. The segmentation algorithm obtains the positions and sizes of symbols and characters, in addition to completing map segmentation and proving useful for patternrecognition. The Raster-to-Vector conversion algorithm obtains topological information necessary to relate cadastral map spatial data to line start points, midpoints, intersection points, and termination points. It consists of four integrated sub-algorithms that remove noise, unify run-length coordinates, and perform synchronous line approximations and logical linkage of line breaks. Straight, angled, and curved lines can then be completely reconstructed for display. Also presented are six indices that verify algorithm and experimental results.
imageprocessing applications and especially those in the area of remotesensing are often characterized by a high degree of complexity. We introduce a general framework, called 'active fusion', that actively ...
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A pixel is not an atom. Most imageprocessing algorithms basically assume that a pixel is not dividable;in other words, its inside is homogeneous consisting of only one classification class. This assumption is, howeve...
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The scattering process of electromagnetic waves is dominated by the match between wavelength and the geometric dimensions of surface structures. With respect to the microwave radar bands millimeter-waves are better ma...
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ISBN:
(纸本)0819421235
The scattering process of electromagnetic waves is dominated by the match between wavelength and the geometric dimensions of surface structures. With respect to the microwave radar bands millimeter-waves are better matched to small surface features of terrain. Therefore this frequency band is able to gain additional information on the terrain of interest. For high resolution imaging SAR is the favorite solution also for millimeter-wave frequencies. Compared to more classical radar bands millimeter-waves offer advantages in the SAR processing, because due to the higher primary resolution at a given antenna aperture sources of image distortions such as range migration or depth of focus can be neglected at these frequencies. Moreover the inherently short aperture time for a given resolution improves the relation to the time constant of flight instabilities and makes motion compensation a simple process. A coherent, polarimetric, high range resolution radar, operating at a nominal frequency of 94 GHz, has been installed onboard an aircraft to allow remotesensing measurements in a side looking synthetic aperture approach. The radar-raw-data were registered together with time code and inertial data of the aircraft and later on evaluated by an off-line SAR-processor. The resulting images then had to undergo an automatic recognition process to extract certain complex targets using a knowledge based production system. The paper describes the measurement system and discusses the evaluation procedures with emphasis on the applied SAR algorithm. Examples of radar images at 94 GHz are shown and samples of patternrecognition derived from the SAR images are shown.
The interpretation of airphotos relies heavily on the identification of textures and spatial patterns. The 2-D wavelet transform can be used to quantify simple patterns for automated classification of pixels in an ima...
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ISBN:
(纸本)0819422061
The interpretation of airphotos relies heavily on the identification of textures and spatial patterns. The 2-D wavelet transform can be used to quantify simple patterns for automated classification of pixels in an image. The transform generates a set of images similar in format to a multispectral image deck, but based on spatial information localized about each pixel. The images in this ''wavelet'' deck each correspond to an analysis of patterns in the original image at different spatial resolutions. For example, where one image in the wavelet deck depends on spatial variations within a 32 x 32 pixel area the next image in the deck contains information on spatial features within a 16 x 16 pixel area Individual pixels in the wavelet deck can be classified using the same classification and patternrecognition algorithms used with multispectral images. Classifications based on the wavelet deck of four airphoto samples using a minimum-distance to mean algorithm and an artificial neural network are presented.
Recently, a new class of structured neural networks (SNNs), explicitly devoted to multisensor remote-sensingimage classification and aimed at allowing the interpretation of the network behaviour, was proposed. Experi...
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In this paper, a novel approach is proposed, which allows for an efficient reduction of the amount of visual data required for representing structural information in the image. This is a multistage architecture which ...
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Telemicroscopy is the central tool to establish a net for telepathology services. To operate such a net in an economical and general available manner the public phone net is selected as communication link. To overcome...
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How to calculate Legendre moments of images by less computation is a very important problem for the application of orthogonal moments in patternrecognition and imageprocessing. In the present paper, we propose the f...
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The proceedings contains 69 articles from the International conference on the Development and Applications of Computer Techniques to Environmental Studies. Topics discussed include: environmental modeling, water pollu...
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The proceedings contains 69 articles from the International conference on the Development and Applications of Computer Techniques to Environmental Studies. Topics discussed include: environmental modeling, water pollution, air pollution, soil pollution, numerical models, state space methods, environmental chemistry, physics, and biology, surface and ground water hydrology, meteorology and climatology, fluid dynamics, satellite data, imageprocessing, patternrecognition, remotesensing, database systems, environmental management and decision analysis, and software implementation.
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