NAME
Image::Leptonica::Func::seedfill
VERSION
version 0.04
seedfill.c
seedfill.c
Binary seedfill (source: Luc Vincent)
PIX *pixSeedfillBinary()
PIX *pixSeedfillBinaryRestricted()
Applications of binary seedfill to find and fill holes,
remove c.c. touching the border and fill bg from border:
PIX *pixHolesByFilling()
PIX *pixFillClosedBorders()
PIX *pixExtractBorderConnComps()
PIX *pixRemoveBorderConnComps()
PIX *pixFillBgFromBorder()
Hole-filling of components to bounding rectangle
PIX *pixFillHolesToBoundingRect()
Gray seedfill (source: Luc Vincent:fast-hybrid-grayscale-reconstruction)
l_int32 pixSeedfillGray()
l_int32 pixSeedfillGrayInv()
Gray seedfill (source: Luc Vincent: sequential-reconstruction algorithm)
l_int32 pixSeedfillGraySimple()
l_int32 pixSeedfillGrayInvSimple()
Gray seedfill variations
PIX *pixSeedfillGrayBasin()
Distance function (source: Luc Vincent)
PIX *pixDistanceFunction()
Seed spread (based on distance function)
PIX *pixSeedspread()
Local extrema:
l_int32 pixLocalExtrema()
static l_int32 pixQualifyLocalMinima()
l_int32 pixSelectedLocalExtrema()
PIX *pixFindEqualValues()
Selection of minima in mask of connected components
PTA *pixSelectMinInConnComp()
Removal of seeded connected components from a mask
PIX *pixRemoveSeededComponents()
ITERATIVE RASTER-ORDER SEEDFILL
The basic method in the Vincent seedfill (aka reconstruction)
algorithm is simple. We describe here the situation for
binary seedfill. Pixels are sampled in raster order in
the seed image. If they are 4-connected to ON pixels
either directly above or to the left, and are not masked
out by the mask image, they are turned on (or remain on).
(Ditto for 8-connected, except you need to check 3 pixels
on the previous line as well as the pixel to the left
on the current line. This is extra computational work
for relatively little gain, so it is preferable
in most situations to use the 4-connected version.)
The algorithm proceeds from UR to LL of the image, and
then reverses and sweeps up from LL to UR.
These double sweeps are iterated until there is no change.
At this point, the seed has entirely filled the region it
is allowed to, as delimited by the mask image.
The grayscale seedfill is a straightforward generalization
of the binary seedfill, and is described in seedfillLowGray().
For some applications, the filled seed will later be OR'd
with the negative of the mask. This is used, for example,
when you flood fill into a 4-connected region of OFF pixels
and you want the result after those pixels are turned ON.
Note carefully that the mask we use delineates which pixels
are allowed to be ON as the seed is filled. We will call this
a "filling mask". As the seed expands, it is repeatedly
ANDed with the filling mask: s & fm. The process can equivalently
be formulated using the inverse of the filling mask, which
we will call a "blocking mask": bm = ~fm. As the seed
expands, the blocking mask is repeatedly used to prevent
the seed from expanding into the blocking mask. This is done
by set subtracting the blocking mask from the expanded seed:
s - bm. Set subtraction of the blocking mask is equivalent
to ANDing with the inverse of the blocking mask: s & (~bm).
But from the inverse relation between blocking and filling
masks, this is equal to s & fm, which proves the equivalence.
For efficiency, the pixels can be taken in larger units
for processing, but still in raster order. It is natural
to take them in 32-bit words. The outline of the work
to be done for 4-cc (not including special cases for boundary
words, such as the first line or the last word in each line)
is as follows. Let the filling mask be m. The
seed is to fill "under" the mask; i.e., limited by an AND
with the mask. Let the current word be w, the word
in the line above be wa, and the previous word in the
current line be wp. Let t be a temporary word that
is used in computation. Note that masking is performed by
w & m. (If we had instead used a "blocking" mask, we
would perform masking by the set subtraction operation,
w - m, which is defined to be w & ~m.)
The entire operation can be implemented with shifts,
logical operations and tests. For each word in the seed image
there are two steps. The first step is to OR the word with
the word above and with the rightmost pixel in wp (call it "x").
Because wp is shifted one pixel to its right, "x" is ORed
to the leftmost pixel of w. We then clip to the ON pixels in
the mask. The result is
t <-- (w | wa | x000... ) & m
We've now finished taking data from above and to the left.
The second step is to allow filling to propagate horizontally
in t, always making sure that it is properly masked at each
step. So if filling can be done (i.e., t is neither all 0s
nor all 1s), iteratively take:
t <-- (t | (t >> 1) | (t << 1)) & m
until t stops changing. Then write t back into w.
Finally, the boundary conditions require we note that in doing
the above steps:
(a) The words in the first row have no wa
(b) The first word in each row has no wp in that row
(c) The last word in each row must be masked so that
pixels don't propagate beyond the right edge of the
actual image. (This is easily accomplished by
setting the out-of-bound pixels in m to OFF.)FUNCTIONS
pixDistanceFunction
PIX * pixDistanceFunction ( PIX *pixs, l_int32 connectivity, l_int32 outdepth, l_int32 boundcond )
pixDistanceFunction()
Input: pixs (1 bpp source)
connectivity (4 or 8)
outdepth (8 or 16 bits for pixd)
boundcond (L_BOUNDARY_BG, L_BOUNDARY_FG)
Return: pixd, or null on error
Notes:
(1) This computes the distance of each pixel from the nearest
background pixel. All bg pixels therefore have a distance of 0,
and the fg pixel distances increase linearly from 1 at the
boundary. It can also be used to compute the distance of
each pixel from the nearest fg pixel, by inverting the input
image before calling this function. Then all fg pixels have
a distance 0 and the bg pixel distances increase linearly
from 1 at the boundary.
(2) The algorithm, described in Leptonica on the page on seed
filling and connected components, is due to Luc Vincent.
In brief, we generate an 8 or 16 bpp image, initialized
with the fg pixels of the input pix set to 1 and the
1-boundary pixels (i.e., the boundary pixels of width 1 on
the four sides set as either:
* L_BOUNDARY_BG: 0
* L_BOUNDARY_FG: max
where max = 0xff for 8 bpp and 0xffff for 16 bpp.
Then do raster/anti-raster sweeps over all pixels interior
to the 1-boundary, where the value of each new pixel is
taken to be 1 more than the minimum of the previously-seen
connected pixels (using either 4 or 8 connectivity).
Finally, set the 1-boundary pixels using the mirrored method;
this removes the max values there.
(3) Using L_BOUNDARY_BG clamps the distance to 0 at the
boundary. Using L_BOUNDARY_FG allows the distance
at the image boundary to "float".
(4) For 4-connected, one could initialize only the left and top
1-boundary pixels, and go all the way to the right
and bottom; then coming back reset left and top. But we
instead use a method that works for both 4- and 8-connected.pixExtractBorderConnComps
PIX * pixExtractBorderConnComps ( PIX *pixs, l_int32 connectivity )
pixExtractBorderConnComps()
Input: pixs (1 bpp)
filling connectivity (4 or 8)
Return: pixd (all pixels in the src that are in connected
components touching the border), or null on errorpixFillBgFromBorder
PIX * pixFillBgFromBorder ( PIX *pixs, l_int32 connectivity )
pixFillBgFromBorder()
Input: pixs (1 bpp)
filling connectivity (4 or 8)
Return: pixd (with the background c.c. touching the border
filled to foreground), or null on error
Notes:
(1) This fills all bg components touching the border to fg.
It is the photometric inverse of pixRemoveBorderConnComps().
(2) Invert the result to get the "holes" left after this fill.
This can be done multiple times, extracting holes within
holes after each pair of fillings. Specifically, this code
peels away n successive embeddings of components:
pix1 = <initial image>
for (i = 0; i < 2 * n; i++) {
pix2 = pixFillBgFromBorder(pix1, 8);
pixInvert(pix2, pix2);
pixDestroy(&pix1);
pix1 = pix2;
}pixFillClosedBorders
PIX * pixFillClosedBorders ( PIX *pixs, l_int32 connectivity )
pixFillClosedBorders()
Input: pixs (1 bpp)
filling connectivity (4 or 8)
Return: pixd (all topologically outer closed borders are filled
as connected comonents), or null on error
Notes:
(1) Start with 1-pixel black border on otherwise white pixd
(2) Subtract input pixs to remove border pixels that were
also on the closed border
(3) Use the inverted pixs as the filling mask to fill in
all the pixels from the outer border to the closed border
on pixs
(4) Invert the result to get the filled component, including
the input border
(5) If the borders are 4-c.c., use 8-c.c. filling, and v.v.
(6) Closed borders within c.c. that represent holes, etc., are filled.pixFillHolesToBoundingRect
PIX * pixFillHolesToBoundingRect ( PIX *pixs, l_int32 minsize, l_float32 maxhfract, l_float32 minfgfract )
pixFillHolesToBoundingRect()
Input: pixs (1 bpp)
minsize (min number of pixels in the hole)
maxhfract (max hole area as fraction of fg pixels in the cc)
minfgfract (min fg area as fraction of bounding rectangle)
Return: pixd (pixs, with some holes possibly filled and some c.c.
possibly expanded to their bounding rects),
or null on error
Notes:
(1) This does not fill holes that are smaller in area than 'minsize'.
(2) This does not fill holes with an area larger than
'maxhfract' times the fg area of the c.c.
(3) This does not expand the fg of the c.c. to bounding rect if
the fg area is less than 'minfgfract' times the area of the
bounding rect.
(4) The decisions are made as follows:
- Decide if we are filling the holes; if so, when using
the fg area, include the filled holes.
- Decide based on the fg area if we are filling to a bounding rect.
If so, do it.
If not, fill the holes if the condition is satisfied.
(5) The choice of minsize depends on the resolution.
(6) For solidifying image mask regions on printed materials,
which tend to be rectangular, values for maxhfract
and minfgfract around 0.5 are reasonable.pixFindEqualValues
PIX * pixFindEqualValues ( PIX *pixs1, PIX *pixs2 )
pixFindEqualValues()
Input: pixs1 (8 bpp)
pixs2 (8 bpp)
Return: pixd (1 bpp mask), or null on error
Notes:
(1) The two images are aligned at the UL corner, and the returned
image has ON pixels where the pixels in pixs1 and pixs2
have equal values.pixHolesByFilling
PIX * pixHolesByFilling ( PIX *pixs, l_int32 connectivity )
pixHolesByFilling()
Input: pixs (1 bpp)
connectivity (4 or 8)
Return: pixd (inverted image of all holes), or null on error
Action:
(1) Start with 1-pixel black border on otherwise white pixd
(2) Use the inverted pixs as the filling mask to fill in
all the pixels from the border to the pixs foreground
(3) OR the result with pixs to have an image with all
ON pixels except for the holes.
(4) Invert the result to get the holes as foreground
Notes:
(1) To get 4-c.c. holes of the 8-c.c. as foreground, use
4-connected filling; to get 8-c.c. holes of the 4-c.c.
as foreground, use 8-connected filling.pixLocalExtrema
l_int32 pixLocalExtrema ( PIX *pixs, l_int32 maxmin, l_int32 minmax, PIX **ppixmin, PIX **ppixmax )
pixLocalExtrema()
Input: pixs (8 bpp)
maxmin (max allowed for the min in a 3x3 neighborhood;
use 0 for default which is to have no upper bound)
minmax (min allowed for the max in a 3x3 neighborhood;
use 0 for default which is to have no lower bound)
&ppixmin (<optional return> mask of local minima)
&ppixmax (<optional return> mask of local maxima)
Return: 0 if OK, 1 on error
Notes:
(1) This gives the actual local minima and maxima.
A local minimum is a pixel whose surrounding pixels all
have values at least as large, and likewise for a local
maximum. For the local minima, @maxmin is the upper
bound for the value of pixs. Likewise, for the local maxima,
@minmax is the lower bound for the value of pixs.
(2) The minima are found by starting with the erosion-and-equality
approach of pixSelectedLocalExtrema(). This is followed
by a qualification step, where each c.c. in the resulting
minimum mask is extracted, the pixels bordering it are
located, and they are queried. If all of those pixels
are larger than the value of that minimum, it is a true
minimum and its c.c. is saved; otherwise the c.c. is
rejected. Note that if a bordering pixel has the
same value as the minimum, it must then have a
neighbor that is smaller, so the component is not a
true minimum.
(3) The maxima are found by inverting the image and looking
for the minima there.
(4) The generated masks can be used as markers for
further operations.pixRemoveBorderConnComps
PIX * pixRemoveBorderConnComps ( PIX *pixs, l_int32 connectivity )
pixRemoveBorderConnComps()
Input: pixs (1 bpp)
filling connectivity (4 or 8)
Return: pixd (all pixels in the src that are not touching the
border) or null on error
Notes:
(1) This removes all fg components touching the border.pixRemoveSeededComponents
PIX * pixRemoveSeededComponents ( PIX *pixd, PIX *pixs, PIX *pixm, l_int32 connectivity, l_int32 bordersize )
pixRemoveSeededComponents()
Input: pixd (<optional>; this can be null or equal to pixm; 1 bpp)
pixs (1 bpp seed)
pixm (1 bpp filling mask)
connectivity (4 or 8)
bordersize (amount of border clearing)
Return: pixd, or null on error
Notes:
(1) This removes each component in pixm for which there is
at least one seed in pixs. If pixd == NULL, this returns
the result in a new pixd. Otherwise, it is an in-place
operation on pixm. In no situation is pixs altered,
because we do the filling with a copy of pixs.
(2) If bordersize > 0, it also clears all pixels within a
distance @bordersize of the edge of pixd. This is here
because pixLocalExtrema() typically finds local minima
at the border. Use @bordersize >= 2 to remove these.pixSeedfillBinary
PIX * pixSeedfillBinary ( PIX *pixd, PIX *pixs, PIX *pixm, l_int32 connectivity )
pixSeedfillBinary()
Input: pixd (<optional>; this can be null, equal to pixs,
or different from pixs; 1 bpp)
pixs (1 bpp seed)
pixm (1 bpp filling mask)
connectivity (4 or 8)
Return: pixd always
Notes:
(1) This is for binary seedfill (aka "binary reconstruction").
(2) There are 3 cases:
(a) pixd == null (make a new pixd)
(b) pixd == pixs (in-place)
(c) pixd != pixs
(3) If you know the case, use these patterns for clarity:
(a) pixd = pixSeedfillBinary(NULL, pixs, ...);
(b) pixSeedfillBinary(pixs, pixs, ...);
(c) pixSeedfillBinary(pixd, pixs, ...);
(4) The resulting pixd contains the filled seed. For some
applications you want to OR it with the inverse of
the filling mask.
(5) The input seed and mask images can be different sizes, but
in typical use the difference, if any, would be only
a few pixels in each direction. If the sizes differ,
the clipping is handled by the low-level function
seedfillBinaryLow().pixSeedfillBinaryRestricted
PIX * pixSeedfillBinaryRestricted ( PIX *pixd, PIX *pixs, PIX *pixm, l_int32 connectivity, l_int32 xmax, l_int32 ymax )
pixSeedfillBinaryRestricted()
Input: pixd (<optional>; this can be null, equal to pixs,
or different from pixs; 1 bpp)
pixs (1 bpp seed)
pixm (1 bpp filling mask)
connectivity (4 or 8)
xmax (max distance in x direction of fill into the mask)
ymax (max distance in y direction of fill into the mask)
Return: pixd always
Notes:
(1) See usage for pixSeedfillBinary(), which has unrestricted fill.
In pixSeedfillBinary(), the filling distance is unrestricted
and can be larger than pixs, depending on the topology of
th mask.
(2) There are occasions where it is useful not to permit the
fill to go more than a certain distance into the mask.
@xmax specifies the maximum horizontal distance allowed
in the fill; @ymax does likewise in the vertical direction.
(3) Operationally, the max "distance" allowed for the fill
is a linear distance from the original seed, independent
of the actual mask topology.
(4) Another formulation of this problem, not implemented,
would use the manhattan distance from the seed, as
determined by a breadth-first search starting at the seed
boundaries and working outward where the mask fg allows.
How this might use the constraints of separate xmax and ymax
is not clear.pixSeedfillGray
l_int32 pixSeedfillGray ( PIX *pixs, PIX *pixm, l_int32 connectivity )
pixSeedfillGray()
Input: pixs (8 bpp seed; filled in place)
pixm (8 bpp filling mask)
connectivity (4 or 8)
Return: 0 if OK, 1 on error
Notes:
(1) This is an in-place filling operation on the seed, pixs,
where the clipping mask is always above or at the level
of the seed as it is filled.
(2) For details of the operation, see the description in
seedfillGrayLow() and the code there.
(3) As an example of use, see the description in pixHDome().
There, the seed is an image where each pixel is a fixed
amount smaller than the corresponding mask pixel.
(4) Reference paper :
L. Vincent, Morphological grayscale reconstruction in image
analysis: applications and efficient algorithms, IEEE Transactions
on Image Processing, vol. 2, no. 2, pp. 176-201, 1993.pixSeedfillGrayBasin
PIX * pixSeedfillGrayBasin ( PIX *pixb, PIX *pixm, l_int32 delta, l_int32 connectivity )
pixSeedfillGrayBasin()
Input: pixb (binary mask giving seed locations)
pixm (8 bpp basin-type filling mask)
delta (amount of seed value above mask)
connectivity (4 or 8)
Return: pixd (filled seed) if OK, null on error
Notes:
(1) This fills from a seed within basins defined by a filling mask.
The seed value(s) are greater than the corresponding
filling mask value, and the result has the bottoms of
the basins raised by the initial seed value.
(2) The seed has value 255 except where pixb has fg (1), which
are the seed 'locations'. At the seed locations, the seed
value is the corresponding value of the mask pixel in pixm
plus @delta. If @delta == 0, we return a copy of pixm.
(3) The actual filling is done using the standard grayscale filling
operation on the inverse of the mask and using the inverse
of the seed image. After filling, we return the inverse of
the filled seed.
(4) As an example of use: pixm can describe a grayscale image
of text, where the (dark) text pixels are basins of
low values; pixb can identify the local minima in pixm (say, at
the bottom of the basins); and delta is the amount that we wish
to raise (lighten) the basins. We construct the seed
(a.k.a marker) image from pixb, pixm and @delta.pixSeedfillGrayInv
l_int32 pixSeedfillGrayInv ( PIX *pixs, PIX *pixm, l_int32 connectivity )
pixSeedfillGrayInv()
Input: pixs (8 bpp seed; filled in place)
pixm (8 bpp filling mask)
connectivity (4 or 8)
Return: 0 if OK, 1 on error
Notes:
(1) This is an in-place filling operation on the seed, pixs,
where the clipping mask is always below or at the level
of the seed as it is filled. Think of filling up a basin
to a particular level, given by the maximum seed value
in the basin. Outside the filled region, the mask
is above the filling level.
(2) Contrast this with pixSeedfillGray(), where the clipping mask
is always above or at the level of the fill. An example
of its use is the hdome fill, where the seed is an image
where each pixel is a fixed amount smaller than the
corresponding mask pixel.
(3) The basin fill, pixSeedfillGrayBasin(), is a special case
where the seed pixel values are generated from the mask,
and where the implementation uses pixSeedfillGray() by
inverting both the seed and mask.pixSeedfillGrayInvSimple
l_int32 pixSeedfillGrayInvSimple ( PIX *pixs, PIX *pixm, l_int32 connectivity )
pixSeedfillGrayInvSimple()
Input: pixs (8 bpp seed; filled in place)
pixm (8 bpp filling mask)
connectivity (4 or 8)
Return: 0 if OK, 1 on error
Notes:
(1) This is an in-place filling operation on the seed, pixs,
where the clipping mask is always below or at the level
of the seed as it is filled. Think of filling up a basin
to a particular level, given by the maximum seed value
in the basin. Outside the filled region, the mask
is above the filling level.
(2) Contrast this with pixSeedfillGraySimple(), where the clipping mask
is always above or at the level of the fill. An example
of its use is the hdome fill, where the seed is an image
where each pixel is a fixed amount smaller than the
corresponding mask pixel.pixSeedfillGraySimple
l_int32 pixSeedfillGraySimple ( PIX *pixs, PIX *pixm, l_int32 connectivity )
pixSeedfillGraySimple()
Input: pixs (8 bpp seed; filled in place)
pixm (8 bpp filling mask)
connectivity (4 or 8)
Return: 0 if OK, 1 on error
Notes:
(1) This is an in-place filling operation on the seed, pixs,
where the clipping mask is always above or at the level
of the seed as it is filled.
(2) For details of the operation, see the description in
seedfillGrayLowSimple() and the code there.
(3) As an example of use, see the description in pixHDome().
There, the seed is an image where each pixel is a fixed
amount smaller than the corresponding mask pixel.
(4) Reference paper :
L. Vincent, Morphological grayscale reconstruction in image
analysis: applications and efficient algorithms, IEEE Transactions
on Image Processing, vol. 2, no. 2, pp. 176-201, 1993.pixSeedspread
PIX * pixSeedspread ( PIX *pixs, l_int32 connectivity )
pixSeedspread()
Input: pixs (8 bpp source)
connectivity (4 or 8)
Return: pixd, or null on error
Notes:
(1) The raster/anti-raster method for implementing this filling
operation was suggested by Ray Smith.
(2) This takes an arbitrary set of nonzero pixels in pixs, which
can be sparse, and spreads (extrapolates) the values to
fill all the pixels in pixd with the nonzero value it is
closest to in pixs. This is similar (though not completely
equivalent) to doing a Voronoi tiling of the image, with a
tile surrounding each pixel that has a nonzero value.
All pixels within a tile are then closer to its "central"
pixel than to any others. Then assign the value of the
"central" pixel to each pixel in the tile.
(3) This is implemented by computing a distance function in parallel
with the fill. The distance function uses free boundary
conditions (assumed maxval outside), and it controls the
propagation of the pixels in pixd away from the nonzero
(seed) values. This is done in 2 traversals (raster/antiraster).
In the raster direction, whenever the distance function
is nonzero, the spread pixel takes on the value of its
predecessor that has the minimum distance value. In the
antiraster direction, whenever the distance function is nonzero
and its value is replaced by a smaller value, the spread
pixel takes the value of the predecessor with the minimum
distance value.
(4) At boundaries where a pixel is equidistant from two
nearest nonzero (seed) pixels, the decision of which value
to use is arbitrary (greedy in search for minimum distance).
This can give rise to strange-looking results, particularly
for 4-connectivity where the L1 distance is computed from
steps in N,S,E and W directions (no diagonals).pixSelectMinInConnComp
l_int32 pixSelectMinInConnComp ( PIX *pixs, PIX *pixm, PTA **ppta, NUMA **pnav )
pixSelectMinInConnComp()
Input: pixs (8 bpp)
pixm (1 bpp)
&pta (<return> pta of min pixel locations)
&nav (<optional return> numa of minima values)
Return: 0 if OK, 1 on error.
Notes:
(1) For each 8 connected component in pixm, this finds
a pixel in pixs that has the lowest value, and saves
it in a Pta. If several pixels in pixs have the same
minimum value, it picks the first one found.
(2) For a mask pixm of true local minima, all pixels in each
connected component have the same value in pixs, so it is
fastest to select one of them using a special seedfill
operation. Not yet implemented.pixSelectedLocalExtrema
l_int32 pixSelectedLocalExtrema ( PIX *pixs, l_int32 mindist, PIX **ppixmin, PIX **ppixmax )
pixSelectedLocalExtrema()
Input: pixs (8 bpp)
mindist (-1 for keeping all pixels; >= 0 specifies distance)
&ppixmin (<return> mask of local minima)
&ppixmax (<return> mask of local maxima)
Return: 0 if OK, 1 on error
Notes:
(1) This selects those local 3x3 minima that are at least a
specified distance from the nearest local 3x3 maxima, and v.v.
for the selected set of local 3x3 maxima.
The local 3x3 minima is the set of pixels whose value equals
the value after a 3x3 brick erosion, and the local 3x3 maxima
is the set of pixels whose value equals the value after
a 3x3 brick dilation.
(2) mindist is the minimum distance allowed between
local 3x3 minima and local 3x3 maxima, in an 8-connected sense.
mindist == 1 keeps all pixels found in step 1.
mindist == 0 removes all pixels from each mask that are
both a local 3x3 minimum and a local 3x3 maximum.
mindist == 1 removes any local 3x3 minimum pixel that touches a
local 3x3 maximum pixel, and likewise for the local maxima.
To make the decision, visualize each local 3x3 minimum pixel
as being surrounded by a square of size (2 * mindist + 1)
on each side, such that no local 3x3 maximum pixel is within
that square; and v.v.
(3) The generated masks can be used as markers for further operations.AUTHOR
Zakariyya Mughal <zmughal@cpan.org>
COPYRIGHT AND LICENSE
This software is copyright (c) 2014 by Zakariyya Mughal.
This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself.