SURF feature descriptor for image analysis

Ashwani Kumar

Article ID: 5643
Vol 6, Issue 2, 2023

VIEWS - 191 (Abstract) 124 (PDF)

Abstract


This paper provides a comprehensive review of SURF (speeded up robust features) feature descriptor, commonly used technique for image feature extraction. The SURF algorithm has obtained significant popularity because to its robustness, efficiency, and invariance to various image transformations. In this paper, an in-depth analysis of the underlying principles of SURF, its key components, and its use in computer vision tasks such as object recognition, image matching, and 3D reconstruction are proposed. Furthermore, we discuss recent advancements and variations of the SURF algorithm and compare it with other popular feature descriptors. Through this review, the aim is to provide a clear understanding of the SURF feature descriptor and its significance in the area of computer vision.


Keywords


SURF (speeded up robust features); image matching; feature detection; scale-invariant; local descriptors; robustness to affine transformations

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References


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DOI: https://doi.org/10.24294/irr.v6i2.5643

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