License plate recognition
License plate recognition using neural networks is an urgent task in the field of computer vision. This is a special case of object detection and classification
How it works
Algorithm 2 recognizes the characters on the number
For this task, convolutional neural networks are usually used, which are able to process images and allocate classes to them.
The process of recognizing license plates using neural networks can be divided into several steps:
1. Image pre-processing: the original license plate image must be transformed in such a way that it is easier to analyze. These can be steps like contrast and lighting normalization, noise filtering, etc.
2. Identification of the region of interest: Quite often, a car number can be located on the image in different places and at different scales. Therefore, you must first select the region of interest in the image where the car number is located.
3. Character segmentation: the resulting region containing the car number must be divided into separate characters.
4. Character recognition: Finally, marked up characters can be subjected to recognition. To do this, you can use convolutional neural networks, which will be trained on a large number of images of car numbers.
Thus, license plate recognition using neural networks is a complex task, but with the right approach, it can be solved very effectively.
The process of recognizing license plates using neural networks can be divided into several steps:
1. Image pre-processing: the original license plate image must be transformed in such a way that it is easier to analyze. These can be steps like contrast and lighting normalization, noise filtering, etc.
2. Identification of the region of interest: Quite often, a car number can be located on the image in different places and at different scales. Therefore, you must first select the region of interest in the image where the car number is located.
3. Character segmentation: the resulting region containing the car number must be divided into separate characters.
4. Character recognition: Finally, marked up characters can be subjected to recognition. To do this, you can use convolutional neural networks, which will be trained on a large number of images of car numbers.
Thus, license plate recognition using neural networks is a complex task, but with the right approach, it can be solved very effectively.
Algorithm 1 detects the presence of a number in the photo
Examples of using
In the course of our work, we have repeatedly solved similar problems, but among all we can single out a solution on light single-board computers.
At the request of the customer, we developed a solution - a smart camera. The device has dimensions of 30x10x10 cm, which includes a camera and a single-board computer on which the number is recognized.
The solution does not require the presence of a server, information about the recognized license plate number and photo is immediately sent from it. The information may be sent to the post office, website, telegram or in any other way.
At the request of the customer, we developed a solution - a smart camera. The device has dimensions of 30x10x10 cm, which includes a camera and a single-board computer on which the number is recognized.
The solution does not require the presence of a server, information about the recognized license plate number and photo is immediately sent from it. The information may be sent to the post office, website, telegram or in any other way.
