Image::Leptonica::Func::dewarp2
version 0.03
dewarp2.c
dewarp2.c Build the page disparity model Build page disparity model l_int32 dewarpBuildPageModel() l_int32 dewarpFindVertDisparity() l_int32 dewarpFindHorizDisparity() PTAA *dewarpGetTextlineCenters() static PTA *dewarpGetMeanVerticals() PTAA *dewarpRemoveShortLines() static l_int32 dewarpGetLineEndpoints() static l_int32 dewarpQuadraticLSF() Build the line disparity model l_int32 dewarpBuildLineModel() Query model status l_int32 dewarpaModelStatus() Rendering helpers static l_int32 pixRenderFlats() static l_int32 pixRenderHorizEndPoints
l_int32 dewarpBuildLineModel ( L_DEWARP *dew, l_int32 opensize, const char *debugfile )
dewarpBuildLineModel() Input: dew opensize (size of opening to remove perpendicular lines) debugfile (use null to skip writing this) Return: 0 if OK, 1 if unable to build the model or on error Notes: (1) This builds the horizontal and vertical disparity arrays for an input of ruled lines, typically for calibration. In book scanning, you could lay the ruled paper over a page. Then for that page and several below it, you can use the disparity correction of the line model to dewarp the pages. (2) The dew has been initialized with the image of ruled lines. These lines must be continuous, but we do a small amount of pre-processing here to insure that. (3) @opensize is typically about 8. It must be larger than the thickness of the lines to be extracted. This is the default value, which is applied if @opensize < 3. (4) Sets vsuccess = 1 and hsuccess = 1 if the vertical and/or horizontal disparity arrays build. (5) Similar to dewarpBuildPageModel(), except here the vertical and horizontal disparity arrays are both built from ruled lines. See notes there.
l_int32 dewarpBuildPageModel ( L_DEWARP *dew, const char *debugfile )
dewarpBuildPageModel() Input: dew debugfile (use null to skip writing this) Return: 0 if OK, 1 if unable to build the model or on error Notes: (1) This is the basic function that builds the horizontal and vertical disparity arrays, which allow determination of the src pixel in the input image corresponding to each dest pixel in the dewarped image. (2) Sets vsuccess = 1 if the vertical disparity array builds. Always attempts to build the horizontal disparity array, even if it will not be requested (useboth == 0). Sets hsuccess = 1 if horizontal disparity builds. (3) The method is as follows: (a) Estimate the points along the centers of all the long textlines. If there are too few lines, no disparity models are built. (b) From the vertical deviation of the lines, estimate the vertical disparity. (c) From the ends of the lines, estimate the horizontal disparity, assuming that the text is made of lines that are left and right justified. (d) One can also compute an additional contribution to the horizontal disparity, inferred from slopes of the top and bottom lines. We do not do this. (4) In more detail for the vertical disparity: (a) Fit a LS quadratic to center locations along each line. This smooths the curves. (b) Sample each curve at a regular interval, find the y-value of the mid-point on each curve, and subtract the sampled curve value from this value. This is the vertical disparity at sampled points along each curve. (c) Fit a LS quadratic to each set of vertically aligned disparity samples. This smooths the disparity values in the vertical direction. Then resample at the same regular interval. We now have a regular grid of smoothed vertical disparity valuels. (5) Once the sampled vertical disparity array is found, it can be interpolated to get a full resolution vertical disparity map. This can be applied directly to the src image pixels to dewarp the image in the vertical direction, making all textlines horizontal. Likewise, the horizontal disparity array is used to left- and right-align the longest textlines.
l_int32 dewarpFindHorizDisparity ( L_DEWARP *dew, PTAA *ptaa )
dewarpFindHorizDisparity() Input: dew ptaa (unsmoothed lines, not vertically ordered) Return: 0 if OK, 1 if vertical disparity array is no built or on error (1) This is not required for a successful model; only the vertical disparity is required. This will not be called if the function to build the vertical disparity fails. (2) Debug output goes to /tmp/dewmod/ for collection into a pdf.
l_int32 dewarpFindVertDisparity ( L_DEWARP *dew, PTAA *ptaa, l_int32 rotflag )
dewarpFindVertDisparity() Input: dew ptaa (unsmoothed lines, not vertically ordered) rotflag (0 if using dew->pixs; 1 if rotated by 90 degrees cw) Return: 0 if OK, 1 on error Notes: (1) This starts with points along the centers of textlines. It does quadratic fitting (and smoothing), first along the lines and then in the vertical direction, to generate the sampled vertical disparity map. This can then be interpolated to full resolution and used to remove the vertical line warping. (2) Use @rotflag == 1 if you are dewarping vertical lines, as is done in dewarpBuildLineModel(). The usual case is for @rotflag == 0. (3) The model fails to build if the vertical disparity fails. This sets the vsuccess flag to 1 on success. (4) Pix debug output goes to /tmp/dewvert/ for collection into a pdf. Non-pix debug output goes to /tmp.
PTAA * dewarpGetTextlineCenters ( PIX *pixs, l_int32 debugflag )
dewarpGetTextlineCenters() Input: pixs (1 bpp) debugflag (1 for debug output) Return: ptaa (of center values of textlines) Notes: (1) This in general does not have a point for each value of x, because there will be gaps between words. It doesn't matter because we will fit a quadratic to the points that we do have.
PTAA * dewarpRemoveShortLines ( PIX *pixs, PTAA *ptaas, l_float32 fract, l_int32 debugflag )
dewarpRemoveShortLines() Input: pixs (1 bpp) ptaas (input lines) fract (minimum fraction of longest line to keep) debugflag Return: ptaad (containing only lines of sufficient length), or null on error
l_int32 dewarpaModelStatus ( L_DEWARPA *dewa, l_int32 pageno, l_int32 *pvsuccess, l_int32 *phsuccess )
dewarpaModelStatus() Input: dewa pageno &vsuccess (<optional return> 1 on success) &hsuccess (<optional return> 1 on success) Return: 0 if OK, 1 on error Notes: (1) This tests if a model has been built, not if it is valid.
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.