SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Robust Image Corner Detection Through Curvature Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Point Matching under Large Image Deformations and Illumination Changes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparametric equations with practical applications in quantigraphic image processing
IEEE Transactions on Image Processing
Interest points of general imbalance
IEEE Transactions on Image Processing
Image watermarking with feature point based synchronization robust to print-scan attack
Journal of Visual Communication and Image Representation
Hi-index | 0.00 |
Most interest point detection algorithms are highly sensitive to illumination variations. This paper presents a method to find interest points robustly even under large non-uniform photometric changes. The method, which we call illumination robust feature extraction transform (IRFET), determines salient interest points in an image by calculating and analyzing contrast signatures. A contrast signature shows the response of an interest point detector with respect to a set of contrast stretching functions. The IRFET is generic and can be used with most interest point detectors. In this paper, we demonstrate that the IRFET improves the repeatability rate of the Harris corner detector significantly (by around 25% on average in the experiments).