#License plate detection python how to
#License plate detection python install
#License plate detection python code
#License plate detection python license

#License plate detection python code

The code for the same is given below img = cv2.resize(img, (620,480) ) gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #convert to grey scale Step 1: Resize the image to the required size and then grayscale it. The test image that I am using for this tutorial is shown below. If you want to jump straight into the code without explanation then you can scroll down to the bottom of this page, where the complete code is provided. We will then use the same image for Character Segmentation and Character Recognition as well.

#License plate detection python license

LetвЂ™s take a sample image of a car and start with detecting the License Plate on that car. The first step in this Raspberry Pi License Plate Reader is to detect the License Plate. We already explained Optical Character Recognition (OCR) using Raspberry Pi. So, we can perform OCR (Optical Character Recognition) on it to detect the number. Character Recognition: Now, the new image that we obtained in the previous step is sure to have some characters (Numbers/Alphabets) written on it. Again this can be done easily using OpenCV.ДЈ. Character Segmentation: Once we have detected the License Plate we have to crop it out and save it as a new image. This gets trickier if the image does not even have a car, in this case we will an additional step to detect the car and then the license plate.Дў. Normally the detection algorithm is trained based on the position of camera and type of number plate used in that particular country. The accuracy can be improved if we know the exact size, color and approximate location of the number plate. We will use the contour option in OpenCV to detect for rectangular objects to find the number plate. License Plate Detection: The first step is to detect the License plate from the car. License Plate Recognition or LPR for short, involves three major steps. Steps involved in License Plate Recognition using Raspberry Pi We will be doing something similar to this to detect the license plate of the car from the image. You can also learn about contours, Blob Detection etc in this Image Segmentation tutorial using OpenCV. This tutorial will not explain how exactly OpenCVВ works, if you are interested in learning Image processing then check out this OpenCV basicsВ and advanced Image processing tutorials. Also Power your Pi with a 2A adapter and connect it to a display monitor for easier debugging.

#License plate detection python install

So make sure to install OpenCV Library on Raspberry PiВ before proceeding with this tutorial. Sounds interesting right!, so LetвЂ™s get started.ДЄs told earlier we will be using the OpenCV Library to detect and recognize faces. We will use some random vehicle images from Google and write a program to recognize the number plate using OpenCV Contour Detection and then read the number from the plate using Tesseract OCR.

#License plate detection python how to

We previously used MATLAB Image processing to read the number plate, today in this article we will learn how to recognize and read License Plate Number from Automobiles using Raspberry Pi and OpenCV. In fact, surveillance companies like Hikvision and many others have already started implementing these features in their products. The video feed from these cameras can be used to perform face recognition, pattern analysis, emotion analysis and much more which would really get it close to something like the вЂњGodвЂ™s EyeвЂќ shown in the FF7 movie. With the advancement in technology especially in Image processing and Machine Learning, it is possible to make these cameras smarter by training them to process information from the Video feed. According to a survey by HIS it is estimated that there were around 245 million security cameras installed and functioning back on 2014, which is like having one security camera for every 30 people on this planet. Today we have video surveillance cameras in schools, hospitals and every other public place to make us feel secured. Security has always been a major concern for mankind.