TY - GEN
T1 - Rotation invariant multi-model scene matching method based on spatial-temporal correlation
AU - Qu, Shengjie
AU - Pan, Quan
AU - Yu, Ying
AU - Cheng, Yongmei
PY - 2010
Y1 - 2010
N2 - In this paper, a rotation invariant multi-model scene matching method is proposed for scene matching aided navigation system. Phase congruency transformation is introduced first to minimize the image difference between multi-model images. Then ring project transformation is processed to make the method invariant to rotation. However, multiple maximum phenomenon is likely to occur after ring project transformation. To solve this problem, a multi-frame spatial-temporal correlation matching method is proposed. Using the spatial-temporal correlation gained from the inertia system or matching of the adjacent interframes, an optimal matching position is gained by maximizing a multi-correlation surface. Afterward, surface fitting method is used to get sub-pixel accuracy matching position. This method, which is invariant to rotation, greatly increases match accuracy. Necessary simulation proves the efficiency of our method.
AB - In this paper, a rotation invariant multi-model scene matching method is proposed for scene matching aided navigation system. Phase congruency transformation is introduced first to minimize the image difference between multi-model images. Then ring project transformation is processed to make the method invariant to rotation. However, multiple maximum phenomenon is likely to occur after ring project transformation. To solve this problem, a multi-frame spatial-temporal correlation matching method is proposed. Using the spatial-temporal correlation gained from the inertia system or matching of the adjacent interframes, an optimal matching position is gained by maximizing a multi-correlation surface. Afterward, surface fitting method is used to get sub-pixel accuracy matching position. This method, which is invariant to rotation, greatly increases match accuracy. Necessary simulation proves the efficiency of our method.
KW - Multi-model scene matching
KW - Phase congruency
KW - Rotation invariant
KW - Spatial-temporal correlation
KW - Sub-pixel accuracy
UR - http://www.scopus.com/inward/record.url?scp=78650538292&partnerID=8YFLogxK
U2 - 10.1109/CISP.2010.5646240
DO - 10.1109/CISP.2010.5646240
M3 - 会议稿件
AN - SCOPUS:78650538292
SN - 9781424465149
T3 - Proceedings - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
SP - 2648
EP - 2652
BT - Proceedings - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
T2 - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
Y2 - 16 October 2010 through 18 October 2010
ER -