The second step in license plate recognition aims to retrieve the characters of the license plate with optical character recognition. For each detected plate, we proceed to segment the plate for each character, and use an Artificial Neural Network (ANN) machine-learning algorithm to recognize the character. Also in this section we will learn how to evaluate a classification algorithm.
First, we obtain a plate image patch as the input to the segmentation OCR function with an equalized histogram, we then need to apply a threshold filter and use this threshold image as the input of a Find contours algorithm; we can see this process in the next figure:
This segmentation process is coded as:
Mat img_threshold;
threshold(input, img_threshold, 60, 255, CV_THRESH_BINARY_INV);
if(DEBUG)
imshow("Threshold plate", img_threshold);
Mat img_contours;
img_threshold.copyTo(img_contours);
//Find contours of possibles characters
vector< vector< Point> > contours...