In this chapter, you learned how an Automatic Number Plate Recognition program works and its two important steps: plate localization and plate recognition.
In the first step, you learned how to segment an image by looking for patches where we may have a plate, and using simple heuristics and the SVM algorithm to make a binary classification for patches with plates and no plates.
In the second step, you learned how to segment using the find contours algorithm, create a deep learning model with TensorFlow, and train and import it into OpenCV. You also learned how to increase the number of samples in your dataset using augmentation techniques.
In the next chapter, you will learn how to create a face recognition application using eigenfaces and deep learning.