Increasing Illumination Invariance of SURF Feature Detector through Color Constancy

• Type: Article in International Conference Proceedings Book
• Date: 2013

Authors

petry, mr (Author) Other; António Paulo Moreira (Author) FEUP; reis, lp (Author) FEUP

Conference proceedings International

Title: PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2013

Pages: 259-270

16th Portuguese Conference on Artificial Intelligence (EPIA)

Angra do Heroismo, PORTUGAL, SEP 09-12, 2013

Indexing

ISI Web of Knowledge - 5 Citations

Scopus - 6 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-008-EFP

DOI: 10.1007/978-3-642-40669-0_23

Abstract (EN): Most of the original image feature detectors are not able to cope with large photometric variations, and their extensions that should improve detection eventually increase the computational cost and introduce more noise to the system. Here we extend the original SURF algorithm increasing its invariance to illumination changes. Our approach uses the local space average color descriptor as working space to detect invariant features. A theoretical analysis demonstrates the impact of distinct photometric variations on the response of blob-like features detected with the SURF algorithm. Experimental results demonstrate the effectiveness of the approach in several illumination conditions including the presence of two or more distinct light sources, variations in color, in offset and scale.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12