an improved local feature descriptor based on sift
Constructing proper descriptors for interest points is a critical aspect for local features related tasks in some computer vision and pattern recognition. This paper proposed to improve the SIFT descriptor by means of combining the second derivative and the gradient magnitude, introducing the polar histogram orientation bin, as well as expending the regions for describing. We present a comparative evaluation of different descriptors and show that our approach provides better results than existing methods and the performance of our descriptors is also confirmed by excellent matching results.
sift interest points matching local descriptors