Authors:
Thales Sehn Korting
;
Leila Maria Garcia Fonseca
;
Luciano Vieira Dutra
and
Felipe Castro da Silva
Affiliation:
National Institute for Space Research (INPE), Brazil
Keyword(s):
Graph Based Segmentation, Re-Segmentation, Urban Imagery, Remote Sensing.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computer Vision, Visualization and Computer Graphics
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Segmentation and Grouping
;
Sensor Networks
;
Signal Processing
;
Signal Processing, Sensors, Systems Modeling and Control
;
Soft Computing
Abstract:
This article presents a new approach for image segmentation applied to urban imagery. The proposed method is called re-segmentation because it uses a previous over-segmented image as input to generate a new set of objects more adequate to the application of interest. For urban objects such as roofs, building and roads, the algorithm tries to generate rectangular objects by merging and cutting operations in a weighted Region Adjacency Graph. Objects whose union generate larger regular objects are merged or otherwise cut. In order to verify the potential of the method, two experimental results using Quickbird images are presented.