Building Computer Vision Projects with OpenCV 4 and C++
by David Millan Escriva, Prateek Joshi, Vinicius G. Mendonca, Roy Shilkrot
Plate detection
In this step, we have to detect all the plates in a current camera frame. To do this task, we divide it in to 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 will apply different filters, morphological operations, contour algorithms, and validations to retrieve parts of the image that could contain a plate.
In the second step (classification), we will apply an SVM classifier to each image patch, our feature. Before creating our main application, we will train with two different classes: plate and non-plate. We will work with parallel frontal view color images with 800 pixels of width and that ...
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