Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Image Analysis and Recognition |
| Untertitel | 8th International Conference, ICIAR 2011, Proceedings, Part I |
| Herausgeber/-innen | Mohamed Kamel, Aurélio Campilho |
| Herausgeber (Verlag) | Springer Verlag |
| Seiten | 161-172 |
| Seitenumfang | 12 |
| ISBN (elektronisch) | 978-3-642-21593-3 |
| ISBN (Print) | 9783642215926 |
| Publikationsstatus | Veröffentlicht - 2011 |
| Veranstaltung | 8th International Conference on Image Analysis and Recognition, ICIAR 2011 - Burnaby, BC, Kanada Dauer: 22 Juni 2011 → 24 Juni 2011 |
Publikationsreihe
| Name | Lecture Notes in Computer Science |
|---|---|
| Band | 6753 |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
We present a method to classify atomic density distributions using CCD images obtained in a quantum optics experiment. The classification is based on the scale invariant detection and precise localization of the central blob in the input image structure. The key idea is the usage of an a priori known shape of the feature in the image scale space. This approach results in higher localization accuracy and more robustness against noise compared to the most accurate state of the art blob region detectors. The classification is done with a success rate of 90% for the experimentally captured images. The results presented here are restricted to special image structures occurring in the atom optics experiment, but the presented methodology can lead to improved results for a wide class of pattern recognition and blob localization problems.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
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Image Analysis and Recognition: 8th International Conference, ICIAR 2011, Proceedings, Part I. Hrsg. / Mohamed Kamel; Aurélio Campilho. Springer Verlag, 2011. S. 161-172 (Lecture Notes in Computer Science; Band 6753).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Classification of Atomic Density Distributions Using Scale Invariant Blob Localization
AU - Cordes, Kai
AU - Topic, Oliver
AU - Scherer, Manuel
AU - Klempt, Carsten
AU - Rosenhahn, Bodo
AU - Ostermann, Jörn
N1 - Funding information: We acknowledge support from the Centre for Quantum Engineering and Space-Time Research QUEST.
PY - 2011
Y1 - 2011
N2 - We present a method to classify atomic density distributions using CCD images obtained in a quantum optics experiment. The classification is based on the scale invariant detection and precise localization of the central blob in the input image structure. The key idea is the usage of an a priori known shape of the feature in the image scale space. This approach results in higher localization accuracy and more robustness against noise compared to the most accurate state of the art blob region detectors. The classification is done with a success rate of 90% for the experimentally captured images. The results presented here are restricted to special image structures occurring in the atom optics experiment, but the presented methodology can lead to improved results for a wide class of pattern recognition and blob localization problems.
AB - We present a method to classify atomic density distributions using CCD images obtained in a quantum optics experiment. The classification is based on the scale invariant detection and precise localization of the central blob in the input image structure. The key idea is the usage of an a priori known shape of the feature in the image scale space. This approach results in higher localization accuracy and more robustness against noise compared to the most accurate state of the art blob region detectors. The classification is done with a success rate of 90% for the experimentally captured images. The results presented here are restricted to special image structures occurring in the atom optics experiment, but the presented methodology can lead to improved results for a wide class of pattern recognition and blob localization problems.
UR - http://www.scopus.com/inward/record.url?scp=79960293227&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21593-3_17
DO - 10.1007/978-3-642-21593-3_17
M3 - Conference contribution
AN - SCOPUS:79960293227
SN - 9783642215926
T3 - Lecture Notes in Computer Science
SP - 161
EP - 172
BT - Image Analysis and Recognition
A2 - Kamel, Mohamed
A2 - Campilho, Aurélio
PB - Springer Verlag
T2 - 8th International Conference on Image Analysis and Recognition, ICIAR 2011
Y2 - 22 June 2011 through 24 June 2011
ER -