The framework consists of C++ code and perl scripts. The C++ code is the 'workhorse', while perl is used to glue together the appropriate command calls for the C++ code.

Extraction of the Dataset

The images are packed in a bzip-compressed archive. On a linux machine, extract it with the command

tar xjvf benchmark_data.tar.bz2

The data requires appproximately 1GB of hard drive space.

The code is bzipped as well, extract it with the command

tar xjvf gt_cmfd.tar.bz2

Library dependencies of the code

To build the code, the system requires a C++ compiler, cmake (minimum version 2.6), boost (tested on boost 1.35 and boost 1.42) and OpenCV version 2.2.

Make sure that these libraries are accessible on your system. Earlier versions of the code have been successfully built on Visual Studio; we expect this to work also with the current version, although not explicitly tested.

Build instructions

The build system cmake creates a Makefile (or Visual Studio solution, if executed on Microsoft Windows). cmake requires a small amount of configuration, in order to build smoothly. In detail, enter the directory of the extracted code, create a build directory and execute cmake:

cd gt_cmfd

mkdir build

cd build

ccmake ../

(under Microsoft Windows, execute cmake, enter gt_cmfd as source directory, and another directory as build directory.)

The cmake interface shows up, press 'c' to configure the data. Once this is done, you are most likely required to enter a configuration value for OpenCV_DIR. Enter here the directory within your openCV 2.2 installation, where the configuration file OpenCVConfig.cmake is located (typically ${opencv_build_dir}/share/opencv). If boost has not been found, you also have to fix these paths manually.

Once all components have been found (type 'c' inbetween to re-configure with your added paths), type 'g' to generate the Makefile. Then, type

make

The binary 'vole' is stored in the newly created subfolder 'bin/', and can be executed by typing

./bin/vole --help

This shows the available subcommands. To get more information about the command line parameters for a particular subcommand, append the subcommand name as first parameter to the program, e.g.

./bin/vole splice --help

Configuration

Using the C++ binaries directly is a bit tedious, as a lot of parameters have to be passed for splicing an image. Thus, we recommend to use the provided perl scripts in the directory 'gt_cmfd/ground_truth_db/scripts/' to generate the command calls.

To create spliced data, the script 'splice_calls.pl' is most important. Before it can be used, edit its configuration files

gt_cmfd/ground_truth_db/scripts/db_setup.pl

and replace the paths for $vole to the C++ binary, and $db_root to your image directory. Consider to use absolute paths, such that the commands can be run from everywhere.

In order to create spliced images, the splicing configuration from

gt_cmfd/ground_truth_db/scripts/splice_config.pl

are used. Four setups are already provided:

• 'nul' for only splicing the images without additional transformations or noise,
• 'rot' to create rotated forgeries
• 'rot_noise' to create forgeries with varying rotation and varying noise
• 'too_much_dont_try' to demonstrate the full bandwith of parameters that can be adjusted

To create the splices, call the splicing generator with an output directory, the selected configuration and an image number (between 1 and 48), e.g.

./gt_cmfd/ground_truth_db/scripts/splice_calls.pl /var/tmp/ nul 10

This prints the command calls to create the spliced images and the associated ground truth. If you want to post-process the ground truth, consider to call ./bin/vole gt_postproc

Note that the iteration over a number of parameters can quickly explode the number of output images, for instance 'too_much_dont_try' creates 7600 calls for every input image, which is clearly too much for a reasonable evaluation.