I am doing a project on the concept of AUTOMATIC NUMBER PLATE RECOGNITION (ANPR) using matlab using artificial neural network for OCR(Optical Character Recognition). Here we initially take an image of car number plate or license plate and perform Image enhancement, Image Segmentation and Character Recognition process to display the license.
Car no plate detector is a very advanced and well-suited project for all engineering graduates of Electronics and Computer Engineering Students. Here we have presented real simulation recording of this project in Matlab Software. Use of this Matlab Project: Actually, this project is the gift given by digital image processing.

Matlab Code For Number Plate Recognition Free Download

Matlab code for number plate recognition free online

The aim of this paper is on presenting a new and simple, but fast and efficient technique for automatic number plate recognition (ANPR) using SIFT (Scale Invariant Feature Transform) features. The proposed system is used to automatically locate and recognize, as a special case, the Jordanian license plates. In the core of our system, SIFT-based template matching technique is used to locate special marks in the license plate.

Matlab Code For Number Plate Recognition Free Online

Upon successful detection of those marks, the license plate is segmented out from the original image and OCR (Optical Character Recognition) is used to recognize the characters or numbers from the plate. Due to the various invariance virtues of SIFT, our method can adaptively deal with various changes in the license plates, such as rotation, scaling, and illumination. Experimental results using real datasets are presented, which show that our system has a good performance.

Hi everyone, I want to develop an OCR model using Keras & Tensorflow to extract the data from Indian Number plates. Knockout font download mac. I have a dataset of about 10000 images of number plates, each image relate to single number plate & the name of the file is the number written in the plate like, 'HR26DH1020'.