TY - GEN
T1 - Choquet integral-based aggregation of image template matching algorithms
AU - Kim, S. H.
AU - Tizhoosh, H. R.
AU - Kamel, M.
N1 - Publisher Copyright:
© 2003 IEEE.
PY - 2003
Y1 - 2003
N2 - Template matching algorithms determine the best matching position of a reference image (template) on a larger image (scene) in either complete or incomplete information environment. In this work, our main objective is to devise a fuzzy integral-based aggregation scheme in an attempt to get more accurate and robust matching, by combining the matching decisions of a finite number of image template matching algorithms, Particularly, Choquet integrals associated with fuzzy measures can be used for handling fuzziness due to incomplete image information. In the present work, a fuzzy integral-based aggregated template matching system is developed on the basis of Choquet integral using belief, plausibility, and probability measure, while being interpreted as an optimistic, a pessimistic, and a noninteracting aggregation, respectively. Finally, to show a validation of Choquet integral-based template matching methods, three individual template matching methods (i,e., MOAD-matcher, SOAD-matcher, and SOSD-matcher) are combined using Choquet integral with respect to different fuzzy measures. Then, performance of these aggregated matchers is compared to individual matchers' performance. It is found that in a complementary sense a Choquet integral-based aggregation of template matching methods gives a better performance compared to the performance of the individual methods.
AB - Template matching algorithms determine the best matching position of a reference image (template) on a larger image (scene) in either complete or incomplete information environment. In this work, our main objective is to devise a fuzzy integral-based aggregation scheme in an attempt to get more accurate and robust matching, by combining the matching decisions of a finite number of image template matching algorithms, Particularly, Choquet integrals associated with fuzzy measures can be used for handling fuzziness due to incomplete image information. In the present work, a fuzzy integral-based aggregated template matching system is developed on the basis of Choquet integral using belief, plausibility, and probability measure, while being interpreted as an optimistic, a pessimistic, and a noninteracting aggregation, respectively. Finally, to show a validation of Choquet integral-based template matching methods, three individual template matching methods (i,e., MOAD-matcher, SOAD-matcher, and SOSD-matcher) are combined using Choquet integral with respect to different fuzzy measures. Then, performance of these aggregated matchers is compared to individual matchers' performance. It is found that in a complementary sense a Choquet integral-based aggregation of template matching methods gives a better performance compared to the performance of the individual methods.
KW - Biomedical measurements
KW - Design engineering
KW - Fuzzy sets
KW - Fuzzy systems
KW - Layout
KW - Machine intelligence
KW - Pattern analysis
KW - Pattern matching
KW - Robustness
KW - System analysis and design
UR - http://www.scopus.com/inward/record.url?scp=84941159871&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84941159871&partnerID=8YFLogxK
U2 - 10.1109/NAFIPS.2003.1226771
DO - 10.1109/NAFIPS.2003.1226771
M3 - Conference contribution
AN - SCOPUS:84941159871
T3 - Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS
SP - 143
EP - 148
BT - NAFIPS 2003 - 22nd International Conference of the North American Fuzzy Information Processing Society - NAFIPS Proceedings
A2 - Walker, Ellen L.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003
Y2 - 24 July 2003 through 26 July 2003
ER -