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.
Titolo: | Efficient template matching for multi-channel images |
Autore/i: | MATTOCCIA, STEFANO; TOMBARI, FEDERICO; DI STEFANO, LUIGI |
Autore/i Unibo: | |
Anno: | 2011 |
Rivista: | |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1016/j.patrec.2010.12.004 |
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. |
Data prodotto definitivo in UGOV: | 2013-06-17 14:35:16 |
Data stato definitivo: | 2017-05-19T19:16:00Z |
Appare nelle tipologie: | 1.01 Articolo in rivista |