License-plate-recognition

Problems include :

• Define license plate container using yolo v4
• Use segmentation to separate each character in the number plate
• Recognize characters in number plates using cnn

Approach

• prepare license plate data and put it through yolo v4 to detect the area containing license plates in the image
• then use image processing methods to separate the characters in the number plate area :
  • adaptiveThreshold ,Connected components analysis, GaussianBlur ...
• use cnn network to recognize characters:
  • Conv2d x2 -> MaxPool -> Dropout -> Conv2d x2 -> MaxPool -> Dropout -> Conv2d x2 -> MaxPool -> Dropout -> Flatten -> Dense -> Dropout -> Softmax(31)

Built With

• Python
• Tensorflow
• Google colab

Data train yolo

link

Data digit train CNN

link

Required settings

add the file yolov4-custom_1000 to the weights folder : link

Result

There are some downsides :

• The image is misrecognized if it is backlit
• When the input image is angled too much, some characters will be misrecognized, There is a solution is to use a transformer network to rotate the image tilted towards the straight image, or you can train more data with the tilted image
• Sometimes misidentified between 8 and B, 0 and D