In this article we will see how we can get the speeded up robust features of image in mahotas. In computer vision, speeded up robust features (SURF) is a patented local feature detector and descriptor. It can be used for tasks such as object recognition, image registration, classification, or 3D reconstruction. It is partly inspired by the scale-invariant feature transform (SIFT) descriptor. For this we are going to use the fluorescent microscopy image from a nuclear segmentation benchmark. We can get the image with the help of command given below
Below is the nuclear_image
In order to do this we will use
Syntax : surf.surf(img)
Argument : It takes image object as argument
Return : It returns numpy.ndarray
Example 1 :
No of points: 217
Example 2 :
No of points: 364
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