DocumentCode :
2283926
Title :
Image analysis methodologies applied to recognition of cartographic features
Author :
Mengucci, Michele
Author_Institution :
Centro de Geo-Sistemas, Instituto Superior Tecnico, Lisbon, Portugal
fYear :
2001
fDate :
2001
Firstpage :
202
Lastpage :
206
Abstract :
One of the many applications of mathematical morphology (MM) is cartographic updating. The automatization of this task is culturally interesting for the importance of an awareness of the actual state of the Earth´s surface, it is scientifically challenging and it has a strong economic interest. The actual technology has enormous computing possibilities that can be focused on this subject through MM The aim of this work is to apply this mathematical theory in order to obtain a method to recognize automatically forms (segmentation) in satellite images, proposing a concept and a sequence of morphological operators based on data belonging both to the spatial domain and to the spectral domain of the treated images. The main item of this thesis is a variant of the concept of the mosaic image and transformations relying on it. These are shown and compared to others in a case study using satellite images of the city of Luanda, in Angola, but they can be easily adapted to any other digital image
Keywords :
cartography; image recognition; image segmentation; mathematical morphology; remote sensing; terrain mapping; Angola; Luanda; cartographic features; image analysis methodologies; mathematical morphology; morphological operators; mosaic image; recognition; satellite images; segmentation; spatial domain; spectral domain; transformations; Digital images; Image analysis; Image edge detection; Image recognition; Image segmentation; Image sequence analysis; Pixel; Remote sensing; Satellites; Surface morphology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Remote Sensing and Data Fusion over Urban Areas, IEEE/ISPRS Joint Workshop 2001
Conference_Location :
Rome
Print_ISBN :
0-7803-7059-7
Type :
conf
DOI :
10.1109/DFUA.2001.985880
Filename :
985880
Link To Document :
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