TY - GEN
T1 - Honey bee mating optimization scheme for active contour model
AU - Horng, Ming Huwi
AU - Chen, Jin Yi
AU - Liou, Ren Jean
PY - 2009
Y1 - 2009
N2 - In this paper, the honey bee mating optimization (HBMO) algorithm is used to improve the detection of the concave region connected with the control points of active contour. In the traditional active contour model (ACM) method, the updating of control point is based on its local energy within a small searching window. As a result, it always results in the failure of precisely searching the boundary concavities. In order to vanquish these drawbacks, the HBMO-based snake scheme is adopted in this paper to search for the optimal position in a lager searching window around each control point. In this proposed scheme, to each active contour there is a chromosome that includes several genes as well as the control points of active contour. These control points are moved iteratively by minimizing the total energy of the active contour. Experimental results reveal that the proposed HBMO-based snake scheme can locate the object boundary of concavity more precisely without requiring large of computational time.
AB - In this paper, the honey bee mating optimization (HBMO) algorithm is used to improve the detection of the concave region connected with the control points of active contour. In the traditional active contour model (ACM) method, the updating of control point is based on its local energy within a small searching window. As a result, it always results in the failure of precisely searching the boundary concavities. In order to vanquish these drawbacks, the HBMO-based snake scheme is adopted in this paper to search for the optimal position in a lager searching window around each control point. In this proposed scheme, to each active contour there is a chromosome that includes several genes as well as the control points of active contour. These control points are moved iteratively by minimizing the total energy of the active contour. Experimental results reveal that the proposed HBMO-based snake scheme can locate the object boundary of concavity more precisely without requiring large of computational time.
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U2 - 10.1109/HIS.2009.42
DO - 10.1109/HIS.2009.42
M3 - Conference contribution
AN - SCOPUS:70450171157
SN - 9780769537450
T3 - Proceedings - 2009 9th International Conference on Hybrid Intelligent Systems, HIS 2009
SP - 174
EP - 179
BT - Proceedings - 2009 9th International Conference on Hybrid Intelligent Systems, HIS 2009
T2 - 2009 9th International Conference on Hybrid Intelligent Systems, HIS 2009
Y2 - 12 August 2009 through 14 August 2009
ER -