Sven Sickert a9c5c11eb0 fixed 'multiple defintions' in felzenszwalb segmentation 8 年之前
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COPYING 2fd42714e0 initialization 12 年之前
Makefile 2fd42714e0 initialization 12 年之前
README 2fd42714e0 initialization 12 年之前
convolve.h 2fd42714e0 initialization 12 年之前
disjoint-set.cpp a9c5c11eb0 fixed 'multiple defintions' in felzenszwalb segmentation 8 年之前
disjoint-set.h a9c5c11eb0 fixed 'multiple defintions' in felzenszwalb segmentation 8 年之前
filter.h a9c5c11eb0 fixed 'multiple defintions' in felzenszwalb segmentation 8 年之前
image.h 2fd42714e0 initialization 12 年之前
imconv.h 2fd42714e0 initialization 12 年之前
imutil.h 2fd42714e0 initialization 12 年之前
misc.h 2fd42714e0 initialization 12 年之前
pnmfile.h 2fd42714e0 initialization 12 年之前
segment-graph.h a9c5c11eb0 fixed 'multiple defintions' in felzenszwalb segmentation 8 年之前
segment-image.h a9c5c11eb0 fixed 'multiple defintions' in felzenszwalb segmentation 8 年之前
segment.cpp 8137977a2f fixed namespace usage 11 年之前

README


Implementation of the segmentation algorithm described in:

Efficient Graph-Based Image Segmentation
Pedro F. Felzenszwalb and Daniel P. Huttenlocher
International Journal of Computer Vision, 59(2) September 2004.

The program takes a color image (PPM format) and produces a segmentation
with a random color assigned to each region.

1) Type "make" to compile "segment".

2) Run "segment sigma k min input output".

The parameters are: (see the paper for details)

sigma: Used to smooth the input image before segmenting it.
k: Value for the threshold function.
min: Minimum component size enforced by post-processing.
input: Input image.
output: Output image.

Typical parameters are sigma = 0.5, k = 500, min = 20.
Larger values for k result in larger components in the result.