1. Algorithm description
1.1 Function
feature extraction and matching using SIFT algorithm
1.2 Input
two pictures in the local folder, respectively named ‘query.jpg’ and
‘reference.jpg’
1.3 Output
shown in the ‘2. Experiment Result’
1.4 Algorithm step
1.4.1 Scale space extremum detection
Search for image positions on all scales. Identify potential points of
interest which are invariant to scale and rotation by means of a Gaussian
differential function.
1.4.2 Key point location
At each candidate location, a fitted fine model is used to determine the
location and scale. The selection of key points depends on their stability.
1.4.3 Direction determination
Based on the local gradient direction of the image, each key point
position is assigned one or more directions. All subsequent operations on
the image data are transformed relative to the direction, scale and position
of key points, thus providing invariance for these transformations.
1.4.4 Key point description
