Evaluating the Robustness of Feature Correspondence using Different Feature Extractors

被引：0

作者：

El-Mashad, Shady Y. ^{[1
]}

Shoukryt, Amin ^{[1
,2
]}

机构：

[1] Egypt Japan Univ Sci & Technol EJUST, Comp Sci & Engn Dept, Alexandria, Egypt

[2] Univ Alexandria, Comp & Syst Engn Dept, Alexandria, Egypt

来源：

2014 19TH INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN AUTOMATION AND ROBOTICS (MMAR) | 2014年

关键词：

Features Matching; Features Extraction; Topological Relations; Graph Matching; Performance Evaluation; Quadratic Assignment Problem;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The importance of choosing a suitable feature detector and descriptor to find the optimal correspondence between two sets of image features has been highlighted. In this direction, this paper presents an evaluation of some well known feature detectors and descriptors; including HARRIS-FREAK, HESSIAN-SURF, MSER-SURF, and FAST-FREAK; in the search for an optimal detector and descriptor pair that best serves the matching procedure between two images. The adopted matching algorithm pays attention not only to the similarity between features but also to the spatial layout in the neighborhood of every matched feature. The experiments conducted on 50 images; representing 10 objects from COIL-100 data-set with extra synthetic deformations; reveal that HARRIS-FREAK's extractor results in better feature correspondence.

引用

页码：316 / 321

页数：6

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