Peer-Reviewed Journal Details
Mandatory Fields
Keyes L.;Winstanley A.
2001
January
Computers, Environment and Urban Systems
Using moment invariants for classifying shapes on large-scale maps
Published
()
Optional Fields
Cartographic data Fourier descriptors Large-scale maps Moment invariants
25
1
119
130
Automated feature extraction and object recognition are large research areas in the field of image processing and computer vision. Recognition is largely based on the matching of descriptions of shapes. Numerous shape description techniques have been developed, such as scalar features (dimension, area, number of corners etc.), Fourier descriptors and moment invariants. These techniques numerically describe shapes independent of translation, scale and rotation and can be easily applied to topographical data. The applicability of the moment invariants technique to classify objects on large-scale maps is described. From the test data used, moments are fairly reliable at distinguishing certain classes of topographic object. However, their effectiveness will increase when fused with the results of other techniques. © 2001 Elsevier Science Ltd. All rights reserved.
0198-9715
10.1016/S0198-9715(00)00041-7
Grant Details