LicenseRecognition is an open source project that recognizes licenses of Car using an Android app to take pictures of license. The project analyzes images, identifies license plates, and send back result to users. The output is the text representation of any license plate characters found in the image.

This project require following ilbraries and tools:

• Ubuntu 12.04
• opencv 2.4.7.1
• tesseract-ocr 3.02.02
• openalpr
• teptonica-1.70
• java 1.7.0_51
• eclipse Kepler Service Release 2
• android 4.1

To install OpenCV 2.4.2 or 2.4.3 on the Ubuntu 12.04 operating system, first install a developer environment to build OpenCV.

sudo apt-get -y install build-essential cmake pkg-config

Install Image I/O libraries

sudo apt-get -y install libjpeg62-dev 
sudo apt-get -y install libtiff4-dev libjasper-dev

Install the GTK dev library

sudo apt-get -y install  libgtk2.0-dev

Install Video I/O libraries

sudo apt-get -y install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev

Optional - install support for Firewire video cameras

sudo apt-get -y install libdc1394-22-dev

Optional - install video streaming libraries

sudo apt-get -y install libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev 

Optional - install the Python development environment and the Python Numerical library

sudo apt-get -y install python-dev python-numpy

Optional - install the parallel code processing library (the Intel tbb library)

sudo apt-get -y install libtbb-dev

Optional - install the Qt dev library

sudo apt-get -y install libqt4-dev

Now download OpenCV 2.4 to wherever you want to compile the source.

mkdir xxx
cd xxx 
wget https://github.com/Itseez/opencv/archive/2.4.7.tar.gz

or

wget http://sourceforge.net/projects/opencvlibrary/files/opencv-unix/2.4.7/opencv-2.4.7.tar.gz

then

tar -zxvf OpenCV-2.4.7.gz

Create and build directory and onfigure OpenCV with cmake. Don't forget the .. part at the end of cmake cmd !!

cd OpenCV-2.4.*
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local
-D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON 
-D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON 
-D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_OPENGL=ON ..

Now compile it

make

And finally install OpenCV

sudo make install

First install the required libraries and tools for compiling.

sudo apt-get install libpng-dev libjpeg-dev libtiff-dev zlib1g-dev
sudo apt-get install gcc g++
sudo apt-get install autoconf automake libtools checkinstall

Install Leptonica from source. The latest version as of writing is 1.70.

wget http://www.leptonica.org/source/leptonica-1.70.tar.gz
tar -zxvf leptonica-1.70.tar.gz
cd leptonica-1.70
./configure
make
sudo checkinstall
sudo ldconfig

Then install Tesseract OCR from source.

wget https://tesseract-ocr.googlecode.com/files/tesseract-ocr-3.02.02.tar.gz
tar -zxvf tesseract-ocr-3.02.02.tar.gz
cd tesseract-ocr
./autogen.sh
./configure
make (this may take a while)
sudo make install
sudo ldconfig

Finally, install the languages you want. Simply place the trained data under /usr/local/share/tessdata. You can do this through wget or FTP upload.

At first, you should clone openalpr from github:

cd <your_work_space>
git clone https://github.com/openalpr/openalpr.git
cd openalpr-master

Then update the src/CMakeLists.txt file in the OpenALPR project. Update the following lines to match the directories of your libraries on your system:

• SET(OpenCV_DIR "<path_to_opencv>")
• SET(Tesseract_DIR "<path_to_esseract-ocr>")

Finally, in the src directory, execute the following commands:

cmake ./
make

Finally, you just need to clone LicenseRecognition project

cd <your_work_space>
git clone https://github.com/yang2012/LicenseRecognition.git

And open it using Eclipse. Then modify Constants.java file to correctly set kUploadImageContainerDirectory and kOpenalprDirectory.

At last, just run it. That's it.

1. support Chinese characters
2. Improve recognition rate

This project is under the MIT License (MIT) https://github.com/yang2012/LicenseRecognition/blob/master/LICENSE