Fast template matching using bounded partial correlation
Machine Vision and Applications
Real-Time Pattern Matching Using Projection Kernels
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast motion estimation algorithm based on the block sum pyramid
IEEE Transactions on Image Processing
A new diamond search algorithm for fast block-matching motion estimation
IEEE Transactions on Image Processing
A multilevel successive elimination algorithm for block matching motion estimation
IEEE Transactions on Image Processing
A fast globally optimal algorithm for template matching using low-resolution pruning
IEEE Transactions on Image Processing
Successive elimination algorithm for motion estimation
IEEE Transactions on Image Processing
A novel four-step search algorithm for fast block motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
Efficient template matching for multi-channel images
Pattern Recognition Letters
Simple low-dimensional features approximating NCC-based image matching
Pattern Recognition Letters
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In this paper we propose an efficient normalized cross correlation (NCC) algorithm for pattern matching based on adaptive multilevel successive elimination. This successive elimination scheme is applied in conjunction with an upper bound for the cross correlation derived from Cauchy-Schwarz inequality. To apply the successive elimination, we partition the summation of cross correlation into different levels with the partition order determined by the gradient energies of the partitioned regions in the template. Thus, this adaptive multi-level successive elimination scheme can be employed to early reject most candidates to reduce the computational cost. Experimental results show the proposed algorithm is very efficient for pattern matching under different lighting conditions.