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Proceedings Paper

Object detection using feature-based template matching
Author(s): Simone Bianco; Marco Buzzelli; Raimondo Schettini
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Paper Abstract

Pattern matching, also known as template matching, is a computationally intensive problem aimed at localizing the instances of a given template within a query image. In this work we present a fast technique for template matching, able to use histogram-based similarity measures on complex descriptors. In particular we will focus on Color Histograms (CH), Histograms of Oriented Gradients (HOG), and Bag of visual Words histograms (BOW). The image is compared with the template via histogram-matching exploiting integral histograms. In order to introduce spatial information, template and candidates are divided into sub-regions, and multiple descriptor sizes are computed. The proposed solution is compared with the Full-Search-equivalent Incremental Dissimilarity Approximations, a state of the art approach, in terms of both accuracy and execution time on different standard datasets.

Paper Details

Date Published: 6 March 2013
PDF: 8 pages
Proc. SPIE 8661, Image Processing: Machine Vision Applications VI, 86610C (6 March 2013); doi: 10.1117/12.2006224
Show Author Affiliations
Simone Bianco, Univ. degli Studi di Milano-Bicocca (Italy)
Marco Buzzelli, Univ. degli Studi di Milano-Bicocca (Italy)
Raimondo Schettini, Univ. degli Studi di Milano-Bicocca (Italy)

Published in SPIE Proceedings Vol. 8661:
Image Processing: Machine Vision Applications VI
Philip R. Bingham; Edmund Y. Lam, Editor(s)

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