Mastering OpenCV with Practical Computer Vision Projects

Plate detection

In this step we have to detect all the plates in the current camera frame. To do this task, we divide it in two main steps: segmentation and segment classification. The feature step is not explained because we use the image patch as a vector feature.

In the first step (segmentation), we apply different filters, morphological operations, contour algorithms, and validations to retrieve those parts of the image that could have a plate.

In the second step (classification), we apply a Support Vector Machine (SVM) classifier to each image patch—our feature. Before creating our main application we train with two different classes—plate and non-plate. We work with parallel frontal-view color images that are 800 pixels wide and taken 2–4 ...