Efficient template matching for multi-channel images

Authors:
Stefano Mattoccia;Federico Tombari;Luigi Di Stefano
Affiliations:
Department of Electronics Computer Science and Systems (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy and Advanced Research Center on Electronic Systems for Information ...;Department of Electronics Computer Science and Systems (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy and Advanced Research Center on Electronic Systems for Information ...;Department of Electronics Computer Science and Systems (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy and Advanced Research Center on Electronic Systems for Information ...
Venue:
Pattern Recognition Letters
Year:
2011

Citing 9
Cited 1

Summed-area tables for texture mapping

SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
The evaluation of normalized cross correlations for defect detection

Pattern Recognition Letters
2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications

2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications
Full-Search-Equivalent Pattern Matching with Incremental Dissimilarity Approximations

IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient NCC-Based Image Matching in Walsh-Hadamard Domain

ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Efficient normalized cross correlation based on adaptive multilevel successive elimination

ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Exploiting inter-frame correlation for fast video to reference image alignment

ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
A fast globally optimal algorithm for template matching using low-resolution pruning

IEEE Transactions on Image Processing
Fast Full-Search Equivalent Template Matching by Enhanced Bounded Correlation

IEEE Transactions on Image Processing

Pattern forced geophysical vector field segmentation based on Clifford FFT

Computers & Geosciences

Quantified Score

Hi-index	0.10

Visualization

Abstract

Template matching is a computationally intensive problem aimed at locating a template within a image. When dealing with images having more than one channel, the computational burden becomes even more dramatic. For this reason, in this paper we investigate on a methodology to speed-up template matching on multi-channel images without deteriorating the outcome of the search. In particular, we propose a fast, exhaustive technique based on the Zero-mean Normalized Cross-Correlation (ZNCC) inspired from previous work related to grayscale images. Experimental testing performed over thousands of template matching instances demonstrates the efficiency of our proposal.