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Technologies 2015, 3(2), 103-110; doi:10.3390/technologies3020103

A Hybrid Feature Extractor using Fast Hessian Detector and SIFT

Ankara University, Computer Engineering, 06830 Ankara, Turkey
Academic Editors: Yudong Zhang and Zhengchao Dong
Received: 3 March 2015 / Revised: 12 May 2015 / Accepted: 12 May 2015 / Published: 15 May 2015
(This article belongs to the Special Issue Medical Imaging & Image Processing)
View Full-Text   |   Download PDF [824 KB, uploaded 15 May 2015]   |  

Abstract

This paper addresses a new hybrid feature extractor algorithm, which in essence integrates a Fast-Hessian detector into the SIFT (Scale Invariant Feature Transform) algorithm. Feature extractors mainly consist of two essential parts: feature detector and descriptor extractor. This study proposes to integrate (Speeded-Up Robust Features) SURF’s hessian detector into the SIFT algorithm so as to boost the total number of true matched pairs. This is a critical requirement in image processing and widely used in various corresponding fields from image stitching to object recognition. The proposed hybrid algorithm has been tested under different experimental conditions and results are quite encouraging in terms of obtaining higher matched pairs and precision score. View Full-Text
Keywords: feature extractor; SIFT; hybrid architecture; fast hessian detector feature extractor; SIFT; hybrid architecture; fast hessian detector
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Güzel, M.S. A Hybrid Feature Extractor using Fast Hessian Detector and SIFT. Technologies 2015, 3, 103-110.

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