Details
| Original language | English |
|---|---|
| Pages (from-to) | 400-405 |
| Number of pages | 6 |
| Journal | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Volume | 38 |
| Publication status | Published - 2010 |
| Event | Joint International Conference on Theory, Data Handling and Modelling in GeoSpatial Information Science - Hong Kong, Hong Kong Duration: 26 May 2010 → 28 May 2010 |
Abstract
An approach to align a linear feature in one dataset with a corresponding feature in another dataset that is considered more accurate is presented. The approach is based on the active contours (snake) concept, but implements the external force as a vector potential field in which case the source of the force is in vector form; further the snake feature is implemented as a non-closed snake. This is different from the conventional implementation of the snake, where the source of the external force is an image and the force is implemented as a gradient flow and usually as a closed snake. In this approach two conditions: the length and alignment conditions have to be satisfied to obtain a good alignment. Whereas the length condition ensures that the length of the snake feature is nearly equal that of the reference feature, the alignment condition requires that the snake and the reference feature are properly aligned. The length condition is achieved by fixing the end points of the snake feature to those of the reference feature. The alignment condition is achieved by segmenting the reference feature so that there is uniform external force from all parts of the feature. One assumption in this approach is that the snake and the reference feature are matched prior to alignment. An outstanding challenge therefore is to find out how to consider the effects of non-corresponding but neighbouring reference features on a snake feature in circumstances where prior matching has not been undertaken.
Keywords
- Feature Alignment, Positional Accuracy Improvement, Snakes, Vector Potential Field
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
- Social Sciences(all)
- Geography, Planning and Development
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In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Vol. 38, 2010, p. 400-405.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Linear feature alignment based on vector potential field
AU - Siriba, David N.
AU - Sester, Monika
PY - 2010
Y1 - 2010
N2 - An approach to align a linear feature in one dataset with a corresponding feature in another dataset that is considered more accurate is presented. The approach is based on the active contours (snake) concept, but implements the external force as a vector potential field in which case the source of the force is in vector form; further the snake feature is implemented as a non-closed snake. This is different from the conventional implementation of the snake, where the source of the external force is an image and the force is implemented as a gradient flow and usually as a closed snake. In this approach two conditions: the length and alignment conditions have to be satisfied to obtain a good alignment. Whereas the length condition ensures that the length of the snake feature is nearly equal that of the reference feature, the alignment condition requires that the snake and the reference feature are properly aligned. The length condition is achieved by fixing the end points of the snake feature to those of the reference feature. The alignment condition is achieved by segmenting the reference feature so that there is uniform external force from all parts of the feature. One assumption in this approach is that the snake and the reference feature are matched prior to alignment. An outstanding challenge therefore is to find out how to consider the effects of non-corresponding but neighbouring reference features on a snake feature in circumstances where prior matching has not been undertaken.
AB - An approach to align a linear feature in one dataset with a corresponding feature in another dataset that is considered more accurate is presented. The approach is based on the active contours (snake) concept, but implements the external force as a vector potential field in which case the source of the force is in vector form; further the snake feature is implemented as a non-closed snake. This is different from the conventional implementation of the snake, where the source of the external force is an image and the force is implemented as a gradient flow and usually as a closed snake. In this approach two conditions: the length and alignment conditions have to be satisfied to obtain a good alignment. Whereas the length condition ensures that the length of the snake feature is nearly equal that of the reference feature, the alignment condition requires that the snake and the reference feature are properly aligned. The length condition is achieved by fixing the end points of the snake feature to those of the reference feature. The alignment condition is achieved by segmenting the reference feature so that there is uniform external force from all parts of the feature. One assumption in this approach is that the snake and the reference feature are matched prior to alignment. An outstanding challenge therefore is to find out how to consider the effects of non-corresponding but neighbouring reference features on a snake feature in circumstances where prior matching has not been undertaken.
KW - Feature Alignment
KW - Positional Accuracy Improvement
KW - Snakes
KW - Vector Potential Field
UR - http://www.scopus.com/inward/record.url?scp=84923700399&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:84923700399
VL - 38
SP - 400
EP - 405
JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SN - 1682-1750
T2 - Joint International Conference on Theory, Data Handling and Modelling in GeoSpatial Information Science
Y2 - 26 May 2010 through 28 May 2010
ER -