期刊名称：Archiwum Fotogrametrii, Kartografii i Teledetekcji
印刷版ISSN：2083-2214
出版年度：2006
卷号：16
语种：English
出版社：Main Board of Association of Polish Surveyors
摘要：This paper presents a novel method of road detection in aerial and satellite imaging. This structural method is based on the concept of profile,meant as a local one-dimensional cross-section (cast) of raster image. We acquire such profiles from the image at different orientation angles and extract from them features well discriminating road pixels from non-road pixels. In particular,we use feature definitions tailored to road characteristics (mostly elongation);these include,among others, mutual similarity of close and equally orientated profiles (road continuity) and symmetry. To improve the precision of analysis,the method computes profiles using sub-pixel sampling. The further part of processing relies on machine learning,in particular,on supervised learning from examples. The algorithm is given a training sample of pixels,for which the decision class assignment (road,non-road) is known. This information may be manually entered by a decision maker (expert) by marking image regions representing road fragments,or alternatively,it may be retrieved from an appropriate module of a geographical information system. Given that information, the algorithm acquires the knowledge from training examples,performing so-called “inductive” learning. That knowledge may be then used to classify the remaining image pixels,for which the decision class assignment is not known. Moreover,the knowledge may be inspected (and potentially corrected) by the decision maker,as it is expressed in a readable form of a decision tree. The paper presents the algorithm in detail,describes its computer implementation,and demonstrates its application to an aerial image of urban area. The obtained results demonstrate the good performance of the method and indicate the usefulness of machine learning approach in analysis of aerial and satellite imagery.
其他摘要：W pracy opisujemy nową metodę wykrywania drogowych tras komunikacyjnych na zobrazowaniu lotniczym lub satelitarnym. Proponowana metoda ma charakter strukturalny i bazuje na koncepcji profilu,rozumianego jako lokalny jednowymiarowy przekrój (rzut) obrazu.
关键词：object detection;satellite and aerial imagery;classification;learning from examples; supervised learning
其他关键词：detekcja;klasyfikacja;uczenie się z przykładów;uczenie nadzorowane
