The following reposiroty contains a benchmark which compares different implementations of the Statistical Region Merging algorithm.
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Given that many image processing and computer vision algorithms are frequently utilized in their 'Pythonic' form, which introduces a notable performance overhead, implementing the algorithm in a highly efficient and fast programming language like C++ was an obvious choice. However, considering the well-known challenges associated with memory management in C++, implementing the algorithm in the Rust programming language presents a compelling alternative, as it offers both high performance and strong memory safety guarantees.
The implementations are benchmarked against the Berkely Image Segmentation Dataset 500 (BSDS500), a widely used dataset for image segmentation (even if for Deep Learning and Computer Vision models),
and then I measure the resource consumption of each implementation.
| Component | Version |
|---|---|
| OpenCV | 4.5.1 |
| C++ | 10.2.1 |
| Rust | 1.81.0 |
| Python | 3.12.4 |
| pip | 24.2 |
| CMake | 3.18.4 |
| Make | 4.3 |