Image::Leptonica::Func::ptafunc1
version 0.04
ptafunc1.c
ptafunc1.c Pta and Ptaa rearrangements PTA *ptaSubsample() l_int32 ptaJoin() l_int32 ptaaJoin() PTA *ptaReverse() PTA *ptaTranspose() PTA *ptaCyclicPerm() PTA *ptaSort() l_int32 ptaGetSortIndex() PTA *ptaSortByIndex() PTA *ptaRemoveDuplicates() PTAA *ptaaSortByIndex() Geometric BOX *ptaGetBoundingRegion() l_int32 *ptaGetRange() PTA *ptaGetInsideBox() PTA *pixFindCornerPixels() l_int32 ptaContainsPt() l_int32 ptaTestIntersection() PTA *ptaTransform() l_int32 ptaPtInsidePolygon() l_float32 l_angleBetweenVectors() Least Squares Fit l_int32 ptaGetLinearLSF() l_int32 ptaGetQuadraticLSF() l_int32 ptaGetCubicLSF() l_int32 ptaGetQuarticLSF() l_int32 ptaNoisyLinearLSF() l_int32 ptaNoisyQuadraticLSF() l_int32 applyLinearFit() l_int32 applyQuadraticFit() l_int32 applyCubicFit() l_int32 applyQuarticFit() Interconversions with Pix l_int32 pixPlotAlongPta() PTA *ptaGetPixelsFromPix() PIX *pixGenerateFromPta() PTA *ptaGetBoundaryPixels() PTAA *ptaaGetBoundaryPixels() Display Pta and Ptaa PIX *pixDisplayPta() PIX *pixDisplayPtaaPattern() PIX *pixDisplayPtaPattern() PTA *ptaReplicatePattern() PIX *pixDisplayPtaa()
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
l_float32 l_angleBetweenVectors ( l_float32 x1, l_float32 y1, l_float32 x2, l_float32 y2 )
l_angleBetweenVectors() Input: x1, y1 (end point of first vector) x2, y2 (end point of second vector) Return: angle (radians), or 0.0 on error Notes: (1) This gives the angle between two vectors, going between vector1 (x1,y1) and vector2 (x2,y2). The angle is swept out from 1 --> 2. If this is clockwise, the angle is positive, but the result is folded into the interval [-pi, pi].
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). Notes: (1) To write on an existing pixs, pixs must be 32 bpp and call with pixd == pixs: pixDisplayPta(pixs, pixs, pta); To write to a new pix, use pixd == NULL and call: pixd = pixDisplayPta(NULL, pixs, pta); (2) On error, returns pixd to avoid losing pixs if called as pixs = pixDisplayPta(pixs, pixs, pta);
PIX * pixDisplayPtaPattern ( PIX *pixd, PIX *pixs, PTA *pta, PIX *pixp, l_int32 cx, l_int32 cy, l_uint32 color )
pixDisplayPtaPattern() Input: pixd (can be same as pixs or null; 32 bpp if in-place) pixs (1, 2, 4, 8, 16 or 32 bpp) pta (giving locations at which the pattern is displayed) pixp (1 bpp pattern to be placed such that its reference point co-locates with each point in pta) cx, cy (reference point in pattern) color (in 0xrrggbb00 format) Return: pixd (32 bpp RGB version of pixs). Notes: (1) To write on an existing pixs, pixs must be 32 bpp and call with pixd == pixs: pixDisplayPtaPattern(pixs, pixs, pta, ...); To write to a new pix, use pixd == NULL and call: pixd = pixDisplayPtaPattern(NULL, pixs, pta, ...); (2) On error, returns pixd to avoid losing pixs if called as pixs = pixDisplayPtaPattern(pixs, pixs, pta, ...); (3) A typical pattern to be used is a circle, generated with generatePtaFilledCircle()
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
PIX * pixDisplayPtaaPattern ( PIX *pixd, PIX *pixs, PTAA *ptaa, PIX *pixp, l_int32 cx, l_int32 cy )
pixDisplayPtaaPattern() Input: pixd (32 bpp) pixs (1, 2, 4, 8, 16 or 32 bpp; 32 bpp if in place) ptaa (giving locations at which the pattern is displayed) pixp (1 bpp pattern to be placed such that its reference point co-locates with each point in pta) cx, cy (reference point in pattern) Return: pixd (32 bpp RGB version of pixs). Notes: (1) To write on an existing pixs, pixs must be 32 bpp and call with pixd == pixs: pixDisplayPtaPattern(pixs, pixs, pta, ...); To write to a new pix, use pixd == NULL and call: pixd = pixDisplayPtaPattern(NULL, pixs, pta, ...); (2) Puts a random color on each pattern associated with a pta. (3) On error, returns pixd to avoid losing pixs if called as pixs = pixDisplayPtaPattern(pixs, pixs, pta, ...); (4) A typical pattern to be used is a circle, generated with generatePtaFilledCircle()
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.
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 @pta. 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 @nafit 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) Either or both &a and &b must be input. They determine the type of line that is fit. (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 @nafit 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 @pta. 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 @nafit 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 @pta. 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 @nafit 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 ptaGetSortIndex ( PTA *ptas, l_int32 sorttype, l_int32 sortorder, NUMA **pnaindex )
ptaGetSortIndex() Input: ptas sorttype (L_SORT_BY_X, L_SORT_BY_Y) sortorder (L_SORT_INCREASING, L_SORT_DECREASING) &naindex (<return> index of sorted order into original array) Return: 0 if OK, 1 on error
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 -1 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' (3) if ptas == NULL, this is a no-op
l_int32 ptaNoisyLinearLSF ( PTA *pta, l_float32 factor, PTA **pptad, l_float32 *pa, l_float32 *pb, l_float32 *pmederr, NUMA **pnafit )
ptaNoisyLinearLSF() Input: pta factor (reject outliers with error greater than this number of medians; typically ~ 3) &ptad (<optional return> with outliers removed) &a (<optional return> slope a of least square fit: y = ax + b) &b (<optional return> intercept b of least square fit) &mederr (<optional return> median error) &nafit (<optional return> numa of least square fit to ptad) Return: 0 if OK, 1 on error Notes: (1) This does a linear least square fit to the set of points in @pta. It then evaluates the errors and removes points whose error is >= factor * median_error. It then re-runs the linear LSF on the resulting points. (2) Either or both &a and &b must be input. They determine the type of line that is fit. (3) The median error can give an indication of how good the fit is likely to be.
l_int32 ptaNoisyQuadraticLSF ( PTA *pta, l_float32 factor, PTA **pptad, l_float32 *pa, l_float32 *pb, l_float32 *pc, l_float32 *pmederr, NUMA **pnafit )
ptaNoisyQuadraticLSF() Input: pta factor (reject outliers with error greater than this number of medians; typically ~ 3) &ptad (<optional return> with outliers removed) &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) &mederr (<optional return> median error) &nafit (<optional return> numa of least square fit to ptad) Return: 0 if OK, 1 on error Notes: (1) This does a quadratic least square fit to the set of points in @pta. It then evaluates the errors and removes points whose error is >= factor * median_error. It then re-runs a quadratic LSF on the resulting points.
l_int32 ptaPtInsidePolygon ( PTA *pta, l_float32 x, l_float32 y, l_int32 *pinside )
ptaPtInsidePolygon() Input: pta (vertices of a polygon) x, y (point to be tested) &inside (<return> 1 if inside; 0 if outside or on boundary) Return: 1 if OK, 0 on error The abs value of the sum of the angles subtended from a point by the sides of a polygon, when taken in order traversing the polygon, is 0 if the point is outside the polygon and 2*pi if inside. The sign will be positive if traversed cw and negative if ccw.
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 * ptaReplicatePattern ( PTA *ptas, PIX *pixp, PTA *ptap, l_int32 cx, l_int32 cy, l_int32 w, l_int32 h )
ptaReplicatePattern() Input: ptas ("sparse" input pta) pixp (<optional> 1 bpp pattern, to be replicated in output pta) ptap (<optional> set of pts, to be replicated in output pta) cx, cy (reference point in pattern) w, h (clipping sizes for output pta) Return: ptad (with all points of replicated pattern), or null on error Notes: (1) You can use either the image @pixp or the set of pts @ptap. (2) The pattern is placed with its reference point at each point in ptas, and all the fg pixels are colleced into ptad. For @pixp, this is equivalent to blitting pixp at each point in ptas, and then converting the resulting pix to a pta.
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 * ptaSortByIndex ( PTA *ptas, NUMA *naindex )
ptaSortByIndex() Input: ptas naindex (na that maps from the new pta to the input pta) Return: ptad (sorted), 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.
PTA * ptaTranspose ( PTA *ptas )
ptaTranspose() Input: ptas Return: ptad (with x and y values swapped), or null on error
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.
l_int32 ptaaJoin ( PTAA *ptaad, PTAA *ptaas, l_int32 istart, l_int32 iend )
ptaaJoin() Input: ptaad (dest ptaa; add to this one) ptaas (source ptaa; add from this one) istart (starting index in ptaas) iend (ending index in ptaas; use -1 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' (3) if ptas == NULL, this is a no-op
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
Zakariyya Mughal <zmughal@cpan.org>
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.
To install Image::Leptonica, copy and paste the appropriate command in to your terminal.
cpanm
cpanm Image::Leptonica
CPAN shell
perl -MCPAN -e shell install Image::Leptonica
For more information on module installation, please visit the detailed CPAN module installation guide.