Identity verification using computer vision for automatic garage door opening

We present a novel system for automatic identification of vehicles as part of an intelligent access control system for a garage entrance. Using a camera in the door, cars are detected and matched to the database of authenticated cars. Once a car is detected, License Plate Recognition (LPR) is applied using character detection and recognition. The found license plate number is matched with the database of authenticated plates. If the car is allowed access, the door will open automatically. The recognition of both cars and characters (LPR) is performed using state-ofthe- art shape descriptors and a linear classifier. Experiments have revealed that 90% of all cars are correctly authenticated from a single image only. Analysis of the computational complexity shows that an embedded implementation allows user authentication within approximately 300ms, which is well within the application constraints

Automatic License Plate Recognition System using Histogram Graph Algorithm

Character recognition is one of the most important applications of image processing. In last couple of decades, the numbers of vehicles have been increasing day by day. With this increase, it is becoming difficult to keep track of each vehicle for the purpose of law enforcement and traffic management. Thus, we need that type of system, which is capable of providing appropriate solutions to the traffic issues and hence this Automatic License Plate Recognition System is developed using Histogram graph algorithm in MATLAB. In which image is captured from camera and converted into Gray scale image for preprocessing .After conversion, dilation process is applied on image. After dilation horizontal and vertical edge processing has been done and passed these histograms through low pass filter. After filtration, image is segmented and license plate is extracted. For detection each character separately from detected license plate smearing algorithm is used

Modelo para la identificación de matrículas en la Ciudad de México mediante algoritmos de aprendizaje automático

Computer vision is one of the fields of Artificial Intelligence that is flourishing because it focuses on the development and improvement of techniques that allow computers to identify, process and classify images, in a way that resembles human vision. This feature makes them an excellent tool for vehicle control systems. For this reason, we developed a system for the recognition of Mexico City license plates using artificial vision techniques, image processing and automatic learning, in order to monitor and speed up response times, when a stolen vehicle is found.La visión artificial es uno de los campos de la Inteligencia Artificial que está en auge debido a que se centra en el desarrollo y mejoramiento de técnicas que permiten a las computadoras identificar, procesar y clasificar las imágenes de una manera similar a lo que hace la visión humana. Esta característica los vuelve una excelente herramienta para los sistemas de control vehicular. Por ello, nosotros desarrollamos un sistema para el reconocimiento de matrículas de la Ciudad de México mediante técnicas de visión artificial, procesamiento de imágenes y aprendizaje automático, con la finalidad de monitorear y agilizar los tiempos de respuesta en caso de encontrar un vehículo robado

Modelo para a identificação de placas na Cidade do México usando algoritmos de aprendizado de máquina

Computer vision is one of the fields of Artificial Intelligence that is flourishing because it focuses on the development and improvement of techniques that allow computers to identify, process and classify images, in a way that resembles human vision. This feature makes them an excellent tool for vehicle control systems. For this reason, we developed a system for the recognition of Mexico City license plates using artificial vision techniques, image processing and automatic learning, in order to monitor and speed up response times, when a stolen vehicle is found.La visión artificial es uno de los campos de la Inteligencia Artificial que está en auge debido a que se centra en el desarrollo y mejoramiento de técnicas que permiten a las computadoras identificar, procesar y clasificar las imágenes de una manera similar a lo que hace la visión humana. Esta característica los vuelve una excelente herramienta para los sistemas de control vehicular. Por ello, nosotros desarrollamos un sistema para el reconocimiento de matrículas de la Ciudad de México mediante técnicas de visión artificial, procesamiento de imágenes y aprendizaje automático, con la finalidad de monitorear y agilizar los tiempos de respuesta en caso de encontrar un vehículo robado.A visão artificial é um dos campos da Inteligência Artificial que está no auge debido a que se centralize no desarrollo e aprimoramento de técnicas que permite que o computador identifique, processe e classifique as imagens de uma maneira similar a lo que hace a visão humanos. Esta característica dos vuelve é uma excelente ferramenta para os sistemas de controle veicular. Por isso, nosotros desarrollamos um sistema para o reconhecimento de matrículas da Ciudad de México com técnicas de visão artificial, processamento de imagens e aprendizado automático, com a finalidad de monitorear e agilizar os tempos de resposta no caso de encontrar um veículo roubado

Identity verification using computer vision for automatic garage door opening

We present a novel system for automatic identification of vehicles as part of an intelligent access control system for a garage entrance. Using a camera in the door, cars are detected and matched to the database of authenticated cars. Once a car is detected, License Plate Recognition (LPR) is applied using character detection and recognition. The found license plate number is matched with the database of authenticated plates. If the car is allowed access, the door will open automatically. The recognition of both cars and characters (LPR) is performed using state-ofthe- art shape descriptors and a linear classifier. Experiments have revealed that 90% of all cars are correctly authenticated from a single image only. Analysis of the computational complexity shows that an embedded implementation allows user authentication within approximately 300ms, which is well within the application constraints