Raspberry Pi Automatic License Plate Recognition with OpenCV 5 : OpenALPR on your Raspberry Pi
In this tutorial I show how to use the OpenALPR, (Open Automatic License Plate Recognition) on your Raspberry Pi. I go over the download, installation, build, and compilation, on your Raspberry Pi.
From your desktop and then transfer it to the pi
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go to this page and download it:
http://www.leptonica.com/download.html
https://code.google.com/p/tesseract-o...
https://tesseract-ocr.googlecode.com/...
https://github.com/openalpr/openalpr/...
scp /home/cesco/Downloads/tesseract-ocr-3.02.02.tar.gz [email protected]:~
scp /home/cesco/Downloads/leptonica-1.69.tar.gz [email protected]:~
scp /home/cesco/Downloads/openalpr.linux.tar.gz [email protected]:~
From the pi:
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wget http://www.leptonica.com/source/lepto... #I used 12.04 to be safe with rpi
http://www.leptonica.com/download.html
wget https://tesseract-ocr.googlecode.com/...
wget https://tesseract-ocr.googlecode.com/...
wget https://github.com/openalpr/openalpr/...
using git:
git clone https://github.com/openalpr/openalpr.git
Dependencies
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sudo apt-get install autoconf automake libtool
sudo apt-get install libpng12-dev
sudo apt-get install libjpeg62-dev
sudo apt-get install libtiff4-dev
sudo apt-get install zlib1g-dev
sudo apt-get install git-core
sudo apt-get install cmake
sudo apt-get install liblog4cplus-dev libcurl3-dev uuid-dev
sudo apt-get install build-essential
First Leptonica, because Tesseract needs Leptonica in order to work
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gunzip leptonica-1.69.tar.gz or in one step (tar -zxvf)
tar -xvf leptonica-1.69.tar
cd leptonica-1.69
sudo ./configure
sudo make install
Second Tesseract:
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gunzip tesseract-ocr-3.02.02.tar.gz or in one step (tar -zxvf)
tar tesseract-ocr-3.02.02.tar
cd tesseract-ocr-3.02.02
./autogen.sh
./configure
make
sudo make install
sudo ldconfig
open your .bashrc file
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sudo nano .bashrc
export TESSDATA_PREFIX=/home/pi/tesseract-ocr/tessdata
OpenCV installation Tutorial
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follow my tutorial
Third OpenALPR
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gunzip openalpr.linux.tar.gz or in one step (tar -zxvf)
cd openalpr
nano CMakeLists.txt
SET(OpenCV_DIR "/usr/local/lib")
SET(Tesseract_DIR "/home/pi/openalpr/libraries/tesseract-ocr")
Tesseract is an optical character recognition engine for various operating systems. It is free software, released under the Apache License, Version 2.0, and development has been sponsored by Google since 2006. Tesseract is considered one of the most accurate open source OCR engines currently available.
The Tesseract engine was originally developed as proprietary software at Hewlett Packard labs in Bristol, England and Greeley, Colorado between 1985 and 1994, with some more changes made in 1996 to port to Windows, and some migration from C to C++ in 1998. A lot of the code was written in C, and then some more was written in C++. Since then all the code has been converted to at least compile with a C++ compiler. Very little work was done in the following decade. It was then released as open source in 2005 by Hewlett Packard and the University of Nevada, Las Vegas (UNLV). Tesseract development has been sponsored by Google since 2006.
OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code.
The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people in their user community and an estimated number of downloads exceeding 7 million. The library is used extensively in companies, research groups and by governmental bodies.
email: [email protected]
twitter: / cesco345
git: https://github.com/cesco345