A Comparative Review of Component Tree Computation Algorithms
From LRDE
Resources
Dataset
Download the image dataset used in this comparison to bench the algorithms (26 Mb).
On-line application.
Compare the performance of the algorithms on an image of your choice and plot the performance curves.
Demo page url: http://olena.lrde.epita.fr/demos/maxtree_comparison.php
Status
Under development. For now, you can only plot curves and show performance of the algorithms on a pre-defined dataset. Benching the algorithms on your own images is still not possible.
Figures
Some results extracted from the paper. Tests conducted on Intel i7 (Intel(R) Core(TM) i7-2600 CPU @ 3.40GHz)
- Error creating thumbnail: Unable to save thumbnail to destination
Comparison of the algorithms on 8-bit images as a function of the size.
- Error creating thumbnail: Unable to save thumbnail to destination
Comparison of the algorithms on 8 Mega-pixels images as a function of the quantization.
- Error creating thumbnail: Unable to save thumbnail to destination
Comparison of the parallel algorithms on a 6.8 Mega-pixels 8-bits image as a function of number of threads. Wall clock time.
- Error creating thumbnail: Unable to save thumbnail to destination
Comparison of the parallel algorithms on a 6.8 Mega-pixels 8-bits image as a function of number of threads. Speedup w.r.t the sequential version.
- Error creating thumbnail: Unable to save thumbnail to destination
Comparison of the parallel algorithms using 8 threads on a 6.8 Mega-pixels image as a function of the quantization.
Figures to answer reviewers requests about:
- Parallel algorithms behaviour on a machine with more cores. It has been tested on a 12-cores (24 logical cores) machine where each processor is an Intel(R) Xeon(R) CPU E5-2620 0 @ 2.00GHz.
- Parallel algorithms behaviour on an AMD processor since some algorithms seem to be more efficient on those architectures. Tests have been conducted on a AMD quad-core AMD Phenom(tm) II X4 945 Processor.
Comparison of the parallel algorithms on a 8-bit 6.8 Mega-pixels image as a function of the number of thread on the 12-cores Intel(R) Xeon(R).
Comparison of the parallel algorithms on a 8-bit 6.8 Mega-pixels image as a function of the number of thread on the quad-core AMD Phenom(tm).
Source files
You can download the archive with the source code.
Dependencies
The applications rely on those external libraries:
- Boost
- libfreeimage
- Intel TBB
You need a c++ 11 compliant compiler (applications have been successfully built with gcc > 4.7 and icc
Building maxtree executables
> tar xjf maxtree-review.tar.bz2 && cd maxtree-review > mkdir build && cd build > cmake .. > make -C apps/maxtree_comparison
It outputs the following executables:
- maxtree_serial_hqueue: Salembier (sequential)
- maxtree_serial_pqueue: Nister (<18bits) / Wilkinson (>18 bits) (sequential)
- maxtree_serial_berger: Berger et al.
- maxtree_serial_ufind_wlc: Berger + level compression
- maxtree_serial_ufind: Berger + level compression enabled if < 18bits
- maxtree_serial_unfindrank: Berger + rank
- maxtree_serial_najman: Najman and Couprie
- maxtree_parallel_hqueue: Salembier (parallel)
- maxtree_parallel_pqueue: Nister (<18bits) / Wilkinson (>18 bits) (parallel)
- maxtree_parallel_ufind: Berger + level compression enabled if < 18bits (parallel)
- maxtree_parallel_unfindrank: Berger + rank (parallel)
- maxtree_parallel_ufind_line: Matas et al. (parallel)
The binaries are then located in apps/maxtree_comparison. For usage and available options, run appname --help where appname is the name of the maxtree algorithm.
$ ./apps/maxtree_comparison/maxtree_serial_berger --help Usage: ./apps/maxtree_comparison/maxtree_serial_berger inputfile Allowed options: --help produce help message --nthread arg (=-1) set number of thread (default: auto) --nbits arg (=8) Set number of bits (default: 8). Quantization of the original is changed. Upper bits are moved left and missing lower bits are generated at random. --ntest arg (=3) set number of runs (default: 3) --sz arg (=0) Set size (number of pixels) (0: original). Resize the image by tiling or cropping the original until matching the number of pixel required. Original ratio width/height is kept.