GitHub - victoroliv2/CCL-GPU: GPU Implementation of some Connected Component Labeling Algorithms

victoroliv2 / CCL-GPU Public

Notifications You must be signed in to change notification settings
Fork 4
Star 21

GPU Implementation of some Connected Component Labeling Algorithms

Notifications

Name		Name	Last commit message	Last commit date
Latest commit History 17 Commits
image_set		image_set
perf_tests		perf_tests
results		results
spiral		spiral
70799.pdf		70799.pdf
A Study on Connected Components Labeling algorithms using GPUs.pdf		A Study on Connected Components Labeling algorithms using GPUs.pdf
LICENSE		LICENSE
README		README
ccl_gold.cpp		ccl_gold.cpp
ccl_lequiv.cu		ccl_lequiv.cu
ccl_naive_prop.cu		ccl_naive_prop.cu
ccl_test.cu		ccl_test.cu
ccl_uf.cu		ccl_uf.cu
distance_transform.cu		distance_transform.cu
distance_transform2.cu		distance_transform2.cu
make.sh		make.sh
pgm.h		pgm.h
run.py		run.py
textures.cuh		textures.cuh

Repository files navigation

Algorithms implemented for "A Study on Connected Components Labeling algorithms using GPUs", published on:

Oliveira, V.M., Lotufo, R.A.: A study on connected components labeling algorithmsusing GPUs. In: SIBGRAPI. vol. 3, p. 4 (2010)

ccl_uf.cu -> new algorithm described in the paper 
ccl_naive_prop.cu -> naive label propagation
ccl_lequiv.cu -> label equivalence
ccl_gold.cu -> ground truth for verification
ccl_test.cu -> runs all 3 on the gpu (main function)
generate_dataset.py -> download dataset used in the paper
run.py -> runs ccl_test on the downloaded dataset
spiral.py -> utilitity to create images with spirals

I don’t have the sources for the CPU CCL implementation used in the paper because it is proprietary (it used SSE2, threads and hand-optimized assembly code).