Automatic number-plate recognition (ANPR) is a technology that uses optical character recognition on images to read vehicle registration plates to create vehicle location data.
ANPR can be used to store the images captured by the cameras as well as the text from the license plate.
Computer and Machine Vision
Facenet: Real-time face recognition using deep learning Tensorflow
The idea is to build application for a real-time face detection and recognition using Tensorflow and a notebook's webcam. The model for face prediction should A mobilenet SSD(single shot multibox detector) based face detector with pretrained model provided powered by tensorflow object detection api trained by NoteFor license plate recognition to work, your camera needs a few specific things:
- The angle of the camera is extremely important, because a camera that's installed too high cannot see the license plate
- The distance from the camera to the car must also be considered - while a camera may be able to zoom in quite a distance, you want to minimize the distance between camera and car
- Lighting is also important - whether you install lights or use the camera's built-in IR, you will need additional lighting at night
- The speed of oncoming traffic must be low enough that the camera has enough time to focus on the license plate
In addition, you'll need to pay attention to the quality of the image. To be used as legal evidence, your video may need to meet standards set by your local law enforcement; one requirement might be that the captured license plate image be at least 15 pixels tall, to ensure clarity.
Web Camera Pro application uses data vision theory to identify objects within video, search through catalogues of images, and extract information out of images.
Object detection deals with detecting instances of semantic objects of a certain class (such as a dog, a human, or a car.) in digital images and videos.
Web Camera Pro - video surveillance
with artificial intelligence.