4. the analysis and manipulation of a digitized image, especially in order to
improve its quality.
5. It’s basically 3 steps
1. Import the Image
2. Analyse and manipulate the Image
3. Output the Image
6. Purpose of Image processing
Visualization - Observe the objects that are not visible.
Image sharpening and restoration - To create a better image.
Image retrieval - Seek for the image of interest.
Measurement of pattern – Measures various objects in an image.
Image Recognition – Distinguish the objects in an image.
7.
8. OpenCV
OpenCV (Open Source Computer Vision) is a library of programming
functions mainly aimed at real-time computer vision,
developed by Intel's research center in Nizhny Novgorod (Russia),
later supported by Willow Garage and now maintained by Itseez.
9. How to install : First Download
https://raw.githubusercontent.com/milq/scripts-ubuntu-debian/master/install-opencv.sh
18. scikit - image
As per scikit-image.org:
“scikit-image is a collection of algorithms for image processing. It is
available free of charge and free of restriction. We pride ourselves on
high-quality, peer-reviewed code, written by an active community of
volunteers.”
21. First steps.
1. Create a file called: hello-image.py
2. Open with notepad
3. Try this code.
22. # imports the thing.
from scikit import data, io, filters
image = data.coins()
edges = filters.sobel(image)
io.imshow(edges)
io.show()
23. Another Example
# imports the thing.
from scikit import data, io, filters
import matplotlib.pyplot as plt
image = data.camera()
val = filters.threshold_otsu(image)
mask = camera - val
# save to disk
plt.imsave('mask.jpg', mask)