נגישות
menu      
חיפוש מתקדם
תחביר
חפש...
הספר "אוצר וולקני"
אודות
תנאי שימוש
ניהול
קהילה:
אסיף מאגר המחקר החקלאי
פותח על ידי קלירמאש פתרונות בע"מ -
Multi-modal registration using a combined similarity measure
Year:
2009
Source of publication :
Advances in Soft Computing
Authors :
אלחנתי, ויקטור
;
.
Volume :
52
Co-Authors:
Wachs, J., Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Be'er-Sheva 84105, Israel
Stern, H., Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Be'er-Sheva 84105, Israel
Burks, T., Agricultural and Biological Engineering, University of Florida, Gainesville, FL 110570, United States
Alchanatis, V., Institute of Agricultural Engineering Volcani Center, Bet-Dagan 50250, Israel
Facilitators :
From page:
159
To page:
168
(
Total pages:
10
)
Abstract:
In this paper we compare similarity measures used for multi-modal registration, and suggest an approach that combines those measures in a way that the registration parameters are weighted according to the strength of each measure. The measures used are: (1) cross correlation normalized, (2) correlation coefficient, (3) correlation coefficient normalized, (4) the Bhattacharyya coefficient, and (5) the mutual information index. The approach is tested on fruit tree registration using multiple sensors (RGB and infra-red). The combination method finds the optimal transformation parameters for each new pair of images to be registered. The method uses a convex linear combination of weighted similarity measures in its objective function. In the future, we plan to use this methodology for an on-tree fruit recognition system in the scope of robotic fruit picking. © 2009 Springer-Verlag Berlin Heidelberg.
Note:
Related Files :
Multi-modal registration
Mutual information
Sensor fusion
Similarity measures
עוד תגיות
תוכן קשור
More details
DOI :
10.1007/978-3-540-88079-0_16
Article number:
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
26026
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:19
Scientific Publication
Multi-modal registration using a combined similarity measure
52
Wachs, J., Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Be'er-Sheva 84105, Israel
Stern, H., Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Be'er-Sheva 84105, Israel
Burks, T., Agricultural and Biological Engineering, University of Florida, Gainesville, FL 110570, United States
Alchanatis, V., Institute of Agricultural Engineering Volcani Center, Bet-Dagan 50250, Israel
Multi-modal registration using a combined similarity measure
In this paper we compare similarity measures used for multi-modal registration, and suggest an approach that combines those measures in a way that the registration parameters are weighted according to the strength of each measure. The measures used are: (1) cross correlation normalized, (2) correlation coefficient, (3) correlation coefficient normalized, (4) the Bhattacharyya coefficient, and (5) the mutual information index. The approach is tested on fruit tree registration using multiple sensors (RGB and infra-red). The combination method finds the optimal transformation parameters for each new pair of images to be registered. The method uses a convex linear combination of weighted similarity measures in its objective function. In the future, we plan to use this methodology for an on-tree fruit recognition system in the scope of robotic fruit picking. © 2009 Springer-Verlag Berlin Heidelberg.
Scientific Publication
You may also be interested in