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Image-Leptonica-0.04
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/ Image::Leptonica::Func::recogident

NAME

Image::Leptonica::Func::recogident

VERSION

version 0.04

recogident.c


            

              
              
recogident.c
    Top-level identification
       l_int32             recogaIdentifyMultiple()
    Segmentation and noise removal
       l_int32             recogSplitIntoCharacters()
       l_int32             recogCorrelationBestRow()
       l_int32             recogCorrelationBestChar()
       static l_int32      pixCorrelationBestShift()
    Low-level identification of single characters
       l_int32             recogaIdentifyPixa()
       l_int32             recogIdentifyPixa()
       l_int32             recogIdentifyPix()
       l_int32             recogSkipIdentify()
    Operations for handling identification results
       static L_RCHA      *rchaCreate()
       l_int32            *rchaDestroy()
       static L_RCH       *rchCreate()
       l_int32            *rchDestroy()
       l_int32             rchaExtract()
       l_int32             rchExtract()
       static l_int32      transferRchToRcha()
       static l_int32      recogaSaveBestRcha()
       static l_int32      recogaTransferRch()
       l_int32             recogTransferRchToDid()
    Preprocessing and filtering
       l_int32             recogProcessToIdentify()
       PIX                *recogPreSplittingFilter()
       PIX                *recogSplittingFilter()
    Postprocessing
       SARRAY             *recogExtractNumbers()
    Modifying recog behavior
       l_int32             recogSetTemplateType()
       l_int32             recogSetScaling()
    Static debug helper
       static void         l_showIndicatorSplitValues()
See recogbasic.c for examples of training a recognizer, which is
required before it can be used for identification.
The character splitter repeatedly does a greedy correlation with each
averaged unscaled template, at all pixel locations along the text to
be identified.  The vertical alignment is between the template
centroid and the (moving) windowed centroid, including a delta of
1 pixel above and below.  The best match then removes part of the
input image, leaving 1 or 2 pieces, which, after filtering,
are put in a queue.  The process ends when the queue is empty.
The filtering is based on the size and aspect ratio of the
remaining pieces; the intent is to remove anything that is
unlikely to be text, such as small pieces and line graphics.
After splitting, the selected segments are identified using
the input parameters that were initially specified for the
recognizer.  Unlike the splitter, which uses the averaged
templates from the unscaled input, the recognizer can use
either all training examples or averaged templates, and these
can be either scaled or unscaled.  These choices are specified
when the recognizer is constructed.

FUNCTIONS

rchDestroy

void rchDestroy ( L_RCH **prch )


            

              
              
rchDestroy()
    Input:  &rch
    Return: void

rchaDestroy

void rchaDestroy ( L_RCHA **prcha )


            

              
              
rchaDestroy()
    Input:  &rcha
    Return: void

rchaExtract

l_int32 rchaExtract ( L_RCHA *rcha, NUMA **pnaindex, NUMA **pnascore, SARRAY **psatext, NUMA **pnasample, NUMA **pnaxloc, NUMA **pnayloc, NUMA **pnawidth )


            

              
              
rchaExtract()
    Input:  rcha
            &naindex (<optional return> indices of best templates)
            &nascore (<optional return> correl scores of best templates)
            &satext (<optional return> character strings of best templates)
            &nasample (<optional return> indices of best samples)
            &naxloc (<optional return> x-locations of templates)
            &nayloc (<optional return> y-locations of templates)
            &nawidth (<optional return> widths of best templates)
    Return: 0 if OK, 1 on error
Notes:
    (1) This returns clones of the number and string arrays.  They must
        be destroyed by the caller.

recogCorrelationBestRow

l_int32 recogCorrelationBestRow ( L_RECOG *recog, PIX *pixs, BOXA **pboxa, NUMA **pnascore, NUMA **pnaindex, SARRAY **psachar, l_int32 debug )


            

              
              
recogCorrelationBestRow()
    Input:  recog (with LUT's pre-computed)
            pixs (typically of multiple touching characters, 1 bpp)
            &boxa (<return> bounding boxs of best fit character)
            &nascores (<optional return> correlation scores)
            &naindex (<optional return> indices of classes)
            &sachar (<optional return> array of character strings)
            debug (1 for results written to pixadb_split)
    Return: 0 if OK, 1 on error
Notes:
    (1) Supervises character matching for (in general) a c.c with
        multiple touching characters.  Finds the best match greedily.
        Rejects small parts that are left over after splitting.
    (2) Matching is to the average, and without character scaling.

recogIdentifyPix

l_int32 recogIdentifyPix ( L_RECOG *recog, PIX *pixs, PIX **ppixdb )


            

              
              
recogIdentifyPix()
    Input:  recog (with LUT's pre-computed)
            pixs (of a single character, 1 bpp)
            &pixdb (<optional return> debug pix showing input and best fit)
    Return: 0 if OK, 1 on error
Notes:
    (1) Basic recognition function for a single character.
    (2) If L_USE_AVERAGE, the matching is only to the averaged bitmaps,
        and the index of the sample is meaningless (0 is returned
        if requested).
    (3) The score is related to the confidence (probability of correct
        identification), in that a higher score is correlated with
        a higher probability.  However, the actual relation between
        the correlation (score) and the probability is not known;
        we call this a "score" because "confidence" can be misinterpreted
        as an actual probability.

recogIdentifyPixa

l_int32 recogIdentifyPixa ( L_RECOG *recog, PIXA *pixa, NUMA *naid, PIX **ppixdb )


            

              
              
recogIdentifyPixa()
    Input:  recog
            pixa (of 1 bpp images to match)
            naid (<optional> indices of components to identify; can be null)
            &pixdb (<optional return> pix showing inputs and best fits)
    Return: 0 if OK, 1 on error
Notes:
    (1) See recogIdentifyPix().  This does the same operation
        for each pix in a pixa, and optionally returns the arrays
        of results (scores, class index and character string)
        for the best correlation match.

recogPreSplittingFilter

PIX * recogPreSplittingFilter ( L_RECOG *recog, PIX *pixs, l_float32 maxasp, l_float32 minaf, l_float32 maxaf, l_int32 debug )


            

              
              
recogPreSplittingFilter()
    Input:  recog
            pixs (1 bpp, single connected component)
            maxasp (maximum asperity ratio (width/height) to be retained)
            minaf (minimum area fraction (|fg|/(w*h)) to be retained)
            maxaf (maximum area fraction (|fg|/(w*h)) to be retained)
            debug (1 to output indicator arrays)
    Return: pixd (with filtered components removed) or null on error

recogProcessToIdentify

PIX * recogProcessToIdentify ( L_RECOG *recog, PIX *pixs, l_int32 pad )


            

              
              
recogProcessToIdentify()
    Input:  recog (with LUT's pre-computed)
            pixs (typ. single character, possibly d > 1 and uncropped)
            pad (extra pixels added to left and right sides)
    Return: pixd (1 bpp, clipped to foreground), or null on error.
Notes:
    (1) This is a lightweight operation to insure that the input
        image is 1 bpp, properly cropped, and padded on each side.
        If bpp > 1, the image is thresholded.

recogSetScaling

l_int32 recogSetScaling ( L_RECOG *recog, l_int32 scalew, l_int32 scaleh )


            

              
              
recogSetScaling()
    Input:  recog
            scalew  (scale all widths to this; use 0 for no scaling)
            scaleh  (scale all heights to this; use 0 for no scaling)
    Return: 0 if OK, 1 on error

recogSetTemplateType

l_int32 recogSetTemplateType ( L_RECOG *recog, l_int32 templ_type )


            

              
              
recogSetTemplateType()
    Input:  recog
            templ_type (L_USE_AVERAGE or L_USE_ALL)
    Return: 0 if OK, 1 on error

recogSkipIdentify

l_int32 recogSkipIdentify ( L_RECOG *recog )


            

              
              
recogSkipIdentify()
    Input:  recog
    Return: 0 if OK, 1 on error
Notes:
    (1) This just writes a "dummy" result with 0 score and empty
        string id into the rch.

recogSplitIntoCharacters

l_int32 recogSplitIntoCharacters ( L_RECOG *recog, PIX *pixs, l_int32 minw, l_int32 minh, BOXA **pboxa, PIXA **ppixa, NUMA **pnaid, l_int32 debug )


            

              
              
recogSplitIntoCharacters()
    Input:  recog
            pixs (1 bpp, contains only mostly deskewed text)
            minw (remove components with width less than this;
                  use -1 for default removing out of band components)
            minh (remove components with height less than this;
                  use -1 for default removing out of band components)
            &boxa (<return> character bounding boxes)
            &pixa (<return> character images)
            &naid (<return> indices of components to identify)
            debug (1 for results written to pixadb_split)
    Return: 0 if OK, 1 on error
Notes:
    (1) This can be given an image that has an arbitrary number
        of text characters.  It does splitting of connected
        components based on greedy correlation matching in
        recogCorrelationBestRow().  The returned pixa includes
        the boxes from which the (possibly split) components
        are extracted.
    (2) If either @minw < 0 or @minh < 0, noise components are
        filtered out, and the returned @naid array is all 1.
        Otherwise, some noise components whose dimensions (w,h)
        satisfy w >= @minw and h >= @minh are allowed through, but
        they are identified in the returned @naid, where they are
        labelled by 0 to indicate that they are not to be run
        through identification.  Retaining the noise components
        provides spatial information that can help applications
        interpret the results.
    (3) In addition to optional filtering of the noise, the
        resulting components are put in row-major (2D) order,
        and the smaller of overlapping components are removed if
        they satisfy conditions of relative size and fractional overlap.
    (4) Note that the spliting function uses unscaled templates
        and does not bother returning the class results and scores.
        Thes are more accurately found later using the scaled templates.

recogSplittingFilter

l_int32 recogSplittingFilter ( L_RECOG *recog, PIX *pixs, l_float32 maxasp, l_float32 minaf, l_float32 maxaf, l_int32 *premove, l_int32 debug )


            

              
              
recogSplittingFilter()
    Input:  recog
            pixs (1 bpp, single connected component)
            maxasp (maximum asperity ratio (width/height) to be retained)
            minaf (minimum area fraction (|fg|/(w*h)) to be retained)
            maxaf (maximum area fraction (|fg|/(w*h)) to be retained)
            &remove (<return> 0 to save, 1 to remove)
            debug (1 to output indicator arrays)
    Return: 0 if OK, 1 on error
Notes:
    (1) We don't want to eliminate sans serif characters like "1" or "l",
        so we use the filter condition requiring both a large area fill
        and a w/h ratio > 1.0.

recogaExtractNumbers

SARRAY * recogaExtractNumbers ( L_RECOGA *recoga, BOXA *boxas, l_float32 scorethresh, l_int32 spacethresh, BOXAA **pbaa, NUMAA **pnaa )


            

              
              
recogaExtractNumbers()
    Input:  recog
            boxas (location of components)
            scorethresh (min score for which we accept a component)
            spacethresh (max horizontal distance allowed between digits,
                         use -1 for default)
            &baa (<optional return> bounding boxes of identified numbers)
            &naa (<optional return> scores of identified digits)
    Return: sa (of identified numbers), or null on error
Notes:
    (1) Each string in the returned sa contains a sequence of ascii
        digits in a number.
    (2) The horizontal distance between boxes (limited by @spacethresh)
        is the negative of the horizontal overlap.
    (3) We allow two digits to be combined if these conditions apply:
          (a) the first is to the left of the second
          (b) the second has a horizontal separation less than @spacethresh
          (c) the vertical overlap >= 0 (vertical separation < 0)
          (d) both have a score that exceeds @scorethresh
    (4) Each numa in the optionally returned naa contains the digit
        scores of a number.  Each boxa in the optionally returned baa
        contains the bounding boxes of the digits in the number.
    (5) Components with a score less than @scorethresh, which may
        be hyphens or other small characters, will signal the
        end of the current sequence of digits in the number.

recogaIdentifyMultiple

l_int32 recogaIdentifyMultiple ( L_RECOGA *recoga, PIX *pixs, l_int32 nitems, l_int32 minw, l_int32 minh, BOXA **pboxa, PIXA **ppixa, PIX **ppixdb, l_int32 debugsplit )


            

              
              
recogaIdentifyMultiple()
    Input:  recoga (with training finished)
            pixs (containing typically a small number of characters)
            nitems (to be identified in pix; use 0 if not known)
            minw (remove components with width less than this;
                  use -1 for removing all noise components)
            minh (remove components with height less than this;
                  use -1 for removing all noise components)
            &boxa (<optional return> locations of identified components)
            &pixa (<optional return> images of identified components)
            &pixdb (<optional return> debug pix: inputs and best fits)
            debugsplit (1 returns pix split debugging images)
    Return: 0 if OK; 1 if more or less than nitems were found (a warning);
            2 on error.
Notes:
    (1) This filters the input pixa, looking for @nitems if requested.
        Set @nitems == 0 if you don't know how many chars to expect.
    (2) This bundles the filtered components into a pixa and calls
        recogIdentifyPixa().  If @nitems > 0, use @minw = -1 and
        @minh = -1 to remove all noise components.  If @nitems > 0
        and it doesn't agree with the number of filtered components
        in pixs, a warning is issued and a 1 is returned.
    (3) Set @minw = 0 and @minh = 0 to get all noise components.
        Set @minw > 0 and/or @minh > 0 to retain selected noise components.
        All noise components are recognized as an empty string with
        a score of 0.0.
    (4) An attempt is made to return 2-dimensional sorted arrays
        of (optional) images and boxes, which can then be used to
        aggregate identified characters into numbers or words.
        One typically wants the pixa, which contains a boxa of the
        extracted subimages.

recogaIdentifyPixa

l_int32 recogaIdentifyPixa ( L_RECOGA *recoga, PIXA *pixa, NUMA *naid, PIX **ppixdb )


            

              
              
recogaIdentifyPixa()
    Input:  recoga
            pixa (of 1 bpp images to match)
            naid (<optional> indices of components to identify; can be null)
            &pixdb (<optional return> pix showing inputs and best fits)
    Return: 0 if OK, 1 on error
Notes:
    (1) See recogIdentifyPixa().  This does the same operation
        for each recog, returning the arrays of results (scores,
        class index and character string) for the best correlation match.

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.