DBC-RGB

Juan Ruiz de Miras. University of Granada - SPAIN. 2025.

Last update: January - 2025

The fractal dimension (FD) is a quantitative parameter widely used to analyze digital images in many application fields such as image segmentation, feature extraction, object recognition, texture analysis, and image compression and denoising, among many others. Color images today can be very large in size, and there is a growing trend toward even larger datasets. This implies that the time required to calculate the FD of such datasets can become extremely long. Here, we provide the source code of a very efficient GPU algorithm, implemented in CUDA, for computing the FD of RGB color images: the DBC-RGB algorithm.

You can download the C++/CUDA source code of the DBC-RGB algorithm by clicking here.

Once unzipped the file dbc-rgb.zip, you will find the following files:

• dbc_rgb25.cu and dbc_rgb25.cuh: CUDA/C++ files with the implementation on GPU of the DBC-RGB algorithm for obtaining FD values between 2 and 5
• dbc_rgb_23.cu and dbc_rgb_23.cuh: CUDA/C++ files with the implementation on GPU of the DBC-RGB algorithm for obtaining FD values between 2 and 3
• test.cpp: example of C++ main file executing the GPU DBC-RGB algorithms
• license.html: terms of the license for the source code of DBC-RGB
• README.txt: text file containing the present information about the program
• images/: folder with sample images for testing the algorithms
• external/: folder with external code for linear regression computation (by geeksforgeeks.org) and reading BMP images (by Arash Partow)

REQUERIMENTS for compilation and execution

Hardware: Computer with a CUDA capable GPU (https://developer.nvidia.com/cuda-gpus)
Software:

• CUDA SDK Toolkit (https://developer.nvidia.com/cuda-toolkit)
• C++ compiler (the binaries folder must be included in the enviroment variable PATH of the OS)

COMPILATION

The test.cpp file can be compiled with the following command: > nvcc -O3 -o test dbc_rgb25.cu dbc_rgb23.cu test.cpp

CITATION

CONTACT AND SUGGESTIONS

FUNDING