Leptonica 1.54
Файл src/ptafunc1.c
#include <string.h>
#include "allheaders.h"

Функции

PTAptaSubsample (PTA *ptas, l_int32 subfactor)
l_int32 ptaJoin (PTA *ptad, PTA *ptas, l_int32 istart, l_int32 iend)
PTAptaReverse (PTA *ptas, l_int32 type)
PTAptaCyclicPerm (PTA *ptas, l_int32 xs, l_int32 ys)
PTAptaSort (PTA *ptas, l_int32 sorttype, l_int32 sortorder, NUMA **pnaindex)
PTAptaRemoveDuplicates (PTA *ptas, l_uint32 factor)
PTAAptaaSortByIndex (PTAA *ptaas, NUMA *naindex)
BOXptaGetBoundingRegion (PTA *pta)
l_int32 ptaGetRange (PTA *pta, l_float32 *pminx, l_float32 *pmaxx, l_float32 *pminy, l_float32 *pmaxy)
PTAptaGetInsideBox (PTA *ptas, BOX *box)
PTApixFindCornerPixels (PIX *pixs)
l_int32 ptaContainsPt (PTA *pta, l_int32 x, l_int32 y)
l_int32 ptaTestIntersection (PTA *pta1, PTA *pta2)
PTAptaTransform (PTA *ptas, l_int32 shiftx, l_int32 shifty, l_float32 scalex, l_float32 scaley)
l_int32 ptaGetLinearLSF (PTA *pta, l_float32 *pa, l_float32 *pb, NUMA **pnafit)
l_int32 ptaGetQuadraticLSF (PTA *pta, l_float32 *pa, l_float32 *pb, l_float32 *pc, NUMA **pnafit)
l_int32 ptaGetCubicLSF (PTA *pta, l_float32 *pa, l_float32 *pb, l_float32 *pc, l_float32 *pd, NUMA **pnafit)
l_int32 ptaGetQuarticLSF (PTA *pta, l_float32 *pa, l_float32 *pb, l_float32 *pc, l_float32 *pd, l_float32 *pe, NUMA **pnafit)
l_int32 applyLinearFit (l_float32 a, l_float32 b, l_float32 x, l_float32 *py)
l_int32 applyQuadraticFit (l_float32 a, l_float32 b, l_float32 c, l_float32 x, l_float32 *py)
l_int32 applyCubicFit (l_float32 a, l_float32 b, l_float32 c, l_float32 d, l_float32 x, l_float32 *py)
l_int32 applyQuarticFit (l_float32 a, l_float32 b, l_float32 c, l_float32 d, l_float32 e, l_float32 x, l_float32 *py)
l_int32 pixPlotAlongPta (PIX *pixs, PTA *pta, l_int32 outformat, const char *title)
PTAptaGetPixelsFromPix (PIX *pixs, BOX *box)
PIXpixGenerateFromPta (PTA *pta, l_int32 w, l_int32 h)
PTAptaGetBoundaryPixels (PIX *pixs, l_int32 type)
PTAAptaaGetBoundaryPixels (PIX *pixs, l_int32 type, l_int32 connectivity, BOXA **pboxa, PIXA **ppixa)
PIXpixDisplayPta (PIX *pixd, PIX *pixs, PTA *pta)
PIXpixDisplayPtaa (PIX *pixs, PTAA *ptaa)

Переменные

static const l_int32 DEFAULT_SPREADING_FACTOR = 7500

Функции

l_int32 applyCubicFit ( l_float32  a,
l_float32  b,
l_float32  c,
l_float32  d,
l_float32  x,
l_float32 py 
)

applyCubicFit()

Input: a, b, c, d (cubic fit coefficients) x &y (<return> y = a * x^3 + b * x^2 + c * x + d) Return: 0 if OK, 1 on error

l_int32 applyLinearFit ( l_float32  a,
l_float32  b,
l_float32  x,
l_float32 py 
)

applyLinearFit()

Input: a, b (linear fit coefficients) x &y (<return> y = a * x + b) Return: 0 if OK, 1 on error

l_int32 applyQuadraticFit ( l_float32  a,
l_float32  b,
l_float32  c,
l_float32  x,
l_float32 py 
)

applyQuadraticFit()

Input: a, b, c (quadratic fit coefficients) x &y (<return> y = a * x^2 + b * x + c) Return: 0 if OK, 1 on error

l_int32 applyQuarticFit ( l_float32  a,
l_float32  b,
l_float32  c,
l_float32  d,
l_float32  e,
l_float32  x,
l_float32 py 
)

applyQuarticFit()

Input: a, b, c, d, e (quartic fit coefficients) x &y (<return> y = a * x^4 + b * x^3 + c * x^2 + d * x + e) Return: 0 if OK, 1 on error

PIX* pixDisplayPta ( PIX pixd,
PIX pixs,
PTA pta 
)

pixDisplayPta()

Input: pixd (can be same as pixs or null; 32 bpp if in-place) pixs (1, 2, 4, 8, 16 or 32 bpp) pta (of path to be plotted) Return: pixd (32 bpp RGB version of pixs, with path in green), or null on error

Notes: (1) To write on an existing pixs, pixs must be 32 bpp and call with pixd == pixs: pixDisplayPta(pixs, pixs, pta); To write on a new pix, set pixd == NULL and call: pixd = pixDisplayPta(NULL, pixs, pta);

PIX* pixDisplayPtaa ( PIX pixs,
PTAA ptaa 
)

pixDisplayPtaa()

Input: pixs (1, 2, 4, 8, 16 or 32 bpp) ptaa (array of paths to be plotted) Return: pixd (32 bpp RGB version of pixs, with paths plotted in different colors), or null on error

PTA* pixFindCornerPixels ( PIX pixs)

pixFindCornerPixels()

Input: pixs (1 bpp) Return: pta, or null on error

Notes: (1) Finds the 4 corner-most pixels, as defined by a search inward from each corner, using a 45 degree line.

PIX* pixGenerateFromPta ( PTA pta,
l_int32  w,
l_int32  h 
)

pixGenerateFromPta()

Input: pta w, h (of pix) Return: pix (1 bpp), or null on error

Notes: (1) Points are rounded to nearest ints. (2) Any points outside (w,h) are silently discarded. (3) Output 1 bpp pix has values 1 for each point in the pta.

l_int32 pixPlotAlongPta ( PIX pixs,
PTA pta,
l_int32  outformat,
const char *  title 
)

pixPlotAlongPta()

Input: pixs (any depth) pta (set of points on which to plot) outformat (GPLOT_PNG, GPLOT_PS, GPLOT_EPS, GPLOT_X11, GPLOT_LATEX) title (<optional> for plot; can be null) Return: 0 if OK, 1 on error

Notes: (1) We remove any existing colormap and clip the pta to the input pixs. (2) This is a debugging function, and does not remove temporary plotting files that it generates. (3) If the image is RGB, three separate plots are generated.

PTAA* ptaaGetBoundaryPixels ( PIX pixs,
l_int32  type,
l_int32  connectivity,
BOXA **  pboxa,
PIXA **  ppixa 
)

ptaaGetBoundaryPixels()

Input: pixs (1 bpp) type (L_BOUNDARY_FG, L_BOUNDARY_BG) connectivity (4 or 8) &boxa (<optional return>=""> bounding boxes of the c.c.) &pixa (<optional return>=""> pixa of the c.c.) Return: ptaa, or null on error

Notes: (1) This generates a ptaa of either fg or bg boundary pixels, where each pta has the boundary pixels for a connected component. (2) We can't simply find all the boundary pixels and then select those within the bounding box of each component, because bounding boxes can overlap. It is necessary to extract and dilate or erode each component separately. Note also that special handling is required for bg pixels when the component touches the pix boundary.

PTAA* ptaaSortByIndex ( PTAA ptaas,
NUMA naindex 
)

ptaaSortByIndex()

Input: ptaas naindex (na that maps from the new ptaa to the input ptaa) Return: ptaad (sorted), or null on error

l_int32 ptaContainsPt ( PTA pta,
l_int32  x,
l_int32  y 
)

ptaContainsPt()

Input: pta x, y (point) Return: 1 if contained, 0 otherwise or on error

PTA* ptaCyclicPerm ( PTA ptas,
l_int32  xs,
l_int32  ys 
)

ptaCyclicPerm()

Input: ptas xs, ys (start point; must be in ptas) Return: ptad (cyclic permutation, starting and ending at (xs, ys), or null on error

Notes: (1) Check to insure that (a) ptas is a closed path where the first and last points are identical, and (b) the resulting pta also starts and ends on the same point (which in this case is (xs, ys).

PTA* ptaGetBoundaryPixels ( PIX pixs,
l_int32  type 
)

ptaGetBoundaryPixels()

Input: pixs (1 bpp) type (L_BOUNDARY_FG, L_BOUNDARY_BG) Return: pta, or null on error

Notes: (1) This generates a pta of either fg or bg boundary pixels.

BOX* ptaGetBoundingRegion ( PTA pta)

ptaGetBoundingRegion()

Input: pta Return: box, or null on error

Notes: (1) This is used when the pta represents a set of points in a two-dimensional image. It returns the box of minimum size containing the pts in the pta.

l_int32 ptaGetCubicLSF ( PTA pta,
l_float32 pa,
l_float32 pb,
l_float32 pc,
l_float32 pd,
NUMA **  pnafit 
)

ptaGetCubicLSF()

Input: pta &a (<optional return>=""> coeff a of LSF: y = ax^3 + bx^2 + cx + d) &b (<optional return>=""> coeff b of LSF) &c (<optional return>=""> coeff c of LSF) &d (<optional return>=""> coeff d of LSF) &nafit (<optional return>=""> numa of least square fit) Return: 0 if OK, 1 on error

Notes: (1) This does a cubic least square fit to the set of points in . That is, it finds coefficients a, b, c and d that minimize:

sum (yi - a*xi*xi*xi -b*xi*xi -c*xi - d)^2 i

Differentiate this expression w/rt a, b, c and d, and solve the resulting four equations for these coefficients in terms of various sums over the input data (xi, yi). The four equations are in the form: f[0][0]a + f[0][1]b + f[0][2]c + f[0][3] = g[0] f[1][0]a + f[1][1]b + f[1][2]c + f[1][3] = g[1] f[2][0]a + f[2][1]b + f[2][2]c + f[2][3] = g[2] f[3][0]a + f[3][1]b + f[3][2]c + f[3][3] = g[3] (2) If is defined, this returns an array of fitted values, corresponding to the two implicit Numa arrays (nax and nay) in pta. Thus, just as you can plot the data in pta as nay vs. nax, you can plot the linear least square fit as nafit vs. nax.

PTA* ptaGetInsideBox ( PTA ptas,
BOX box 
)

ptaGetInsideBox()

Input: ptas (input pts) box Return: ptad (of pts in ptas that are inside the box), or null on error

l_int32 ptaGetLinearLSF ( PTA pta,
l_float32 pa,
l_float32 pb,
NUMA **  pnafit 
)

ptaGetLinearLSF()

Input: pta &a (<optional return>=""> slope a of least square fit: y = ax + b) &b (<optional return>=""> intercept b of least square fit) &nafit (<optional return>=""> numa of least square fit) Return: 0 if OK, 1 on error

Notes: (1) At least one of: &a and &b must not be null. (2) If both &a and &b are defined, this returns a and b that minimize:

sum (yi - axi -b)^2 i

The method is simple: differentiate this expression w/rt a and b, and solve the resulting two equations for a and b in terms of various sums over the input data (xi, yi). (3) We also allow two special cases, where either a = 0 or b = 0: (a) If &a is given and &b = null, find the linear LSF that goes through the origin (b = 0). (b) If &b is given and &a = null, find the linear LSF with zero slope (a = 0). (4) If is defined, this returns an array of fitted values, corresponding to the two implicit Numa arrays (nax and nay) in pta. Thus, just as you can plot the data in pta as nay vs. nax, you can plot the linear least square fit as nafit vs. nax.

PTA* ptaGetPixelsFromPix ( PIX pixs,
BOX box 
)

ptaGetPixelsFromPix()

Input: pixs (1 bpp) box (<optional> can be null) Return: pta, or null on error

Notes: (1) Generates a pta of fg pixels in the pix, within the box. If box == NULL, it uses the entire pix.

l_int32 ptaGetQuadraticLSF ( PTA pta,
l_float32 pa,
l_float32 pb,
l_float32 pc,
NUMA **  pnafit 
)

ptaGetQuadraticLSF()

Input: pta &a (<optional return>=""> coeff a of LSF: y = ax^2 + bx + c) &b (<optional return>=""> coeff b of LSF: y = ax^2 + bx + c) &c (<optional return>=""> coeff c of LSF: y = ax^2 + bx + c) &nafit (<optional return>=""> numa of least square fit) Return: 0 if OK, 1 on error

Notes: (1) This does a quadratic least square fit to the set of points in . That is, it finds coefficients a, b and c that minimize:

sum (yi - a*xi*xi -b*xi -c)^2 i

The method is simple: differentiate this expression w/rt a, b and c, and solve the resulting three equations for these coefficients in terms of various sums over the input data (xi, yi). The three equations are in the form: f[0][0]a + f[0][1]b + f[0][2]c = g[0] f[1][0]a + f[1][1]b + f[1][2]c = g[1] f[2][0]a + f[2][1]b + f[2][2]c = g[2] (2) If is defined, this returns an array of fitted values, corresponding to the two implicit Numa arrays (nax and nay) in pta. Thus, just as you can plot the data in pta as nay vs. nax, you can plot the linear least square fit as nafit vs. nax.

l_int32 ptaGetQuarticLSF ( PTA pta,
l_float32 pa,
l_float32 pb,
l_float32 pc,
l_float32 pd,
l_float32 pe,
NUMA **  pnafit 
)

ptaGetQuarticLSF()

Input: pta &a (<optional return>=""> coeff a of LSF: y = ax^4 + bx^3 + cx^2 + dx + e) &b (<optional return>=""> coeff b of LSF) &c (<optional return>=""> coeff c of LSF) &d (<optional return>=""> coeff d of LSF) &e (<optional return>=""> coeff e of LSF) &nafit (<optional return>=""> numa of least square fit) Return: 0 if OK, 1 on error

Notes: (1) This does a quartic least square fit to the set of points in . That is, it finds coefficients a, b, c, d and 3 that minimize:

sum (yi - a*xi*xi*xi*xi -b*xi*xi*xi -c*xi*xi - d*xi - e)^2 i

Differentiate this expression w/rt a, b, c, d and e, and solve the resulting five equations for these coefficients in terms of various sums over the input data (xi, yi). The five equations are in the form: f[0][0]a + f[0][1]b + f[0][2]c + f[0][3] + f[0][4] = g[0] f[1][0]a + f[1][1]b + f[1][2]c + f[1][3] + f[1][4] = g[1] f[2][0]a + f[2][1]b + f[2][2]c + f[2][3] + f[2][4] = g[2] f[3][0]a + f[3][1]b + f[3][2]c + f[3][3] + f[3][4] = g[3] f[4][0]a + f[4][1]b + f[4][2]c + f[4][3] + f[4][4] = g[4] (2) If is defined, this returns an array of fitted values, corresponding to the two implicit Numa arrays (nax and nay) in pta. Thus, just as you can plot the data in pta as nay vs. nax, you can plot the linear least square fit as nafit vs. nax.

l_int32 ptaGetRange ( PTA pta,
l_float32 pminx,
l_float32 pmaxx,
l_float32 pminy,
l_float32 pmaxy 
)

ptaGetRange()

Input: pta &minx (<optional return>=""> min value of x) &maxx (<optional return>=""> max value of x) &miny (<optional return>=""> min value of y) &maxy (<optional return>=""> max value of y) Return: 0 if OK, 1 on error

Notes: (1) We can use pts to represent pairs of floating values, that are not necessarily tied to a two-dimension region. For example, the pts can represent a general function y(x).

l_int32 ptaJoin ( PTA ptad,
PTA ptas,
l_int32  istart,
l_int32  iend 
)

ptaJoin()

Input: ptad (dest pta; add to this one) ptas (source pta; add from this one) istart (starting index in ptas) iend (ending index in ptas; use 0 to cat all) Return: 0 if OK, 1 on error

Notes: (1) istart < 0 is taken to mean 'read from the start' (istart = 0) (2) iend <= 0 means 'read to the end'

PTA* ptaRemoveDuplicates ( PTA ptas,
l_uint32  factor 
)

ptaRemoveDuplicates()

Input: ptas (assumed to be integer values) factor (should be larger than the largest point value; use 0 for default) Return: ptad (with duplicates removed), or null on error

PTA* ptaReverse ( PTA ptas,
l_int32  type 
)

ptaReverse()

Input: ptas type (0 for float values; 1 for integer values) Return: ptad (reversed pta), or null on error

PTA* ptaSort ( PTA ptas,
l_int32  sorttype,
l_int32  sortorder,
NUMA **  pnaindex 
)

ptaSort()

Input: ptas sorttype (L_SORT_BY_X, L_SORT_BY_Y) sortorder (L_SORT_INCREASING, L_SORT_DECREASING) &naindex (<optional return>=""> index of sorted order into original array) Return: ptad (sorted version of ptas), or null on error

PTA* ptaSubsample ( PTA ptas,
l_int32  subfactor 
)

ptaSubsample()

Input: ptas subfactor (subsample factor, >= 1) Return: ptad (evenly sampled pt values from ptas, or null on error

l_int32 ptaTestIntersection ( PTA pta1,
PTA pta2 
)

ptaTestIntersection()

Input: pta1, pta2 Return: bval which is 1 if they have any elements in common; 0 otherwise or on error.

PTA* ptaTransform ( PTA ptas,
l_int32  shiftx,
l_int32  shifty,
l_float32  scalex,
l_float32  scaley 
)

ptaTransform()

Input: pta shiftx, shifty scalex, scaley Return: pta, or null on error

Notes: (1) Shift first, then scale.


Переменные

const l_int32 DEFAULT_SPREADING_FACTOR = 7500 [static]