OpenCV 4 with Python Blueprints - Second Edition

Detecting features in an image with SURF

In the remainder of this chapter, we will make use of the SURF detector. The SURF algorithm can be roughly divided into two distinct steps, which are detecting points of interest and formulating a descriptor.

SURF relies on the Hessian corner detector for interest point detection, which requires the setting of a minimal minhessianThreshold. This threshold determines how large the output from the Hessian filter must be in order for a point to be used as an interesting point.

When the value is larger, fewer interest points are obtained, but they are theoretically more salient and vice versa. Feel free to experiment with different values.

In this chapter, we will choose a value of 400, as we did earlier ...