DocumentCode
1645670
Title
Image segmentation for appearance-based self-localisation
Author
Zingaretti, P. ; Bossoletti, L.
fYear
2001
Firstpage
113
Lastpage
118
Abstract
The paper describes a segmentation technique that well fits to an appearance-based self-localisation. In an appearance-based approach robot positioning is performed without using explicit object models. The choice of the representation of image appearances is fundamental. We use image-domain features, as opposed to interpreted characteristics of the scene, and we adopt feature vectors including both the chromatic attributes of colour sets and their mutual spatial relationships. To obtain the colour sets we perform image segmentation by autothresholding the colour histograms and taking into account what the results are addressed to. The experimental results indicate that the method performs well for a variety of environments
Keywords
feature extraction; image colour analysis; image representation; image segmentation; robot vision; statistical analysis; appearance-based self-localisation; autothresholding; chromatic attributes; colour histograms; colour sets; feature vectors; image representation; image segmentation; image-domain features; robot positioning; spatial relationship; Data mining; Feature extraction; Histograms; Image segmentation; Layout; Mobile robots; Navigation; Path planning; Robot sensing systems; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Analysis and Processing, 2001. Proceedings. 11th International Conference on
Conference_Location
Palermo
Print_ISBN
0-7695-1183-X
Type
conf
DOI
10.1109/ICIAP.2001.956994
Filename
956994
Link To Document