2D object recognition: a comparative analysis of SIFT, SURF and ORB feature descriptors

Object recognition is a key research area in the field of image processing and computer vision, which recognizes the object in an image and provides a proper label. In the paper, three popular feature descriptor algorithms that are Scale Invariant Feature Transform (SIFT), Speeded Up Robust Feature...

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Veröffentlicht in:	Multimedia tools and applications Jg. 80; H. 12; S. 18839 - 18857
Hauptverfasser:	Bansal, Monika, Kumar, Munish, Kumar, Manish
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.05.2021 Springer Nature B.V
Schlagworte:	Algorithms Classification Cluster analysis Clustering Comparative analysis Computer Communication Networks Computer Science Computer vision Data Structures and Information Theory Decision trees Feature extraction Feature recognition Image processing Multimedia Information Systems Object recognition Special Purpose and Application-Based Systems Two dimensional analysis Two dimensional models Vector quantization K-means SURF SIFT LPP ORB PCA
ISSN:	1380-7501, 1573-7721
Online-Zugang:	Volltext
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