Detecting features with SURF

Speeded Up Robust Features (SURF) is a patented algorithm similar to and inspired by SIFT (refer to the Applying Scale-Invariant Feature Transform recipe). SURF was introduced in 2006 and uses Haar wavelets (refer to the Applying the discrete wavelet transform recipe). The greatest advantage of SURF is that it is faster than SIFT.

Take a look at the following equations:

Detecting features with SURF

The algorithm steps are as follows:

  1. Transform the image if necessary to get the grayscale equivalent.
  2. Calculate the integral image at different scales, which is the sum of the pixels above and to the left of a pixel, as shown in equation (11.1). The integral ...

Get Python Data Analysis Cookbook now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.