In this chapter, we will discuss the application of machine learning techniques in image processing. We will define machine learning and learn about two of its algorithms, supervised and unsupervised. Then, we will continue our discussion on the application of a few popular unsupervised machine learning techniques, such as clustering, and problems such as image segmentation.

We will also be looking at applications of supervised machine learning techniques for problems such as image classification and object detection. We will be using a very popular library, scikit-learn, along with scikit-image and Python-OpenCV (cv2) to implement machine learning algorithms for image processing. This chapter is going to give you insight into machine learning algorithms and the problems they solve.

 The topics to be covered in this chapter are as follows:

• Supervised versus unsupervised learning 
• Unsupervised machine learning—clustering, PCA, and eigenfaces
• Supervised machine learning—image classification with the handwritten digits dataset
• Supervised machine learning—object detection