/*!
* \brief pixGetWordsInTextlines()
*
* \param[in] pixs 1 bpp, typ. 75 - 150 ppi
* \param[in] minwidth, minheight of saved components; smaller are discarded
* \param[in] maxwidth, maxheight of saved components; larger are discarded
* \param[out] pboxad word boxes sorted in textline line order
* \param[out] ppixad word images sorted in textline line order
* \param[out] pnai index of textline for each word
* \return 0 if OK, 1 on error
*
* <pre>
* Notes:
* (1) The input should be at a resolution of between 75 and 150 ppi.
* (2) The four size constraints on saved components are all
* scaled by %reduction.
* (3) The result are word images (and their b.b.), extracted in
* textline order, at either full res or 2x reduction,
* and with a numa giving the textline index for each word.
* (4) The pixa and boxa interfaces should make this type of
* application simple to put together. The steps are:
* ~ generate first estimate of word masks
* ~ get b.b. of these, and remove the small and big ones
* ~ extract pixa of the word images, using the b.b.
* ~ sort actual word images in textline order (2d)
* ~ flatten them to a pixa (1d), saving the textline index
* for each pix
* (5) In an actual application, it may be desirable to pre-filter
* the input image to remove large components, to extract
* single columns of text, and to deskew them. For example,
* to remove both large components and small noisy components
* that can interfere with the statistics used to estimate
* parameters for segmenting by words, but still retain text lines,
* the following image preprocessing can be done:
* Pix *pixt = pixMorphSequence(pixs, "c40.1", 0);
* Pix *pixf = pixSelectBySize(pixt, 0, 60, 8,
* L_SELECT_HEIGHT, L_SELECT_IF_LT, NULL);
* pixAnd(pixf, pixf, pixs); // the filtered image
* The closing turns text lines into long blobs, but does not
* significantly increase their height. But if there are many
* small connected components in a dense texture, this is likely
* to generate tall components that will be eliminated in pixf.
* </pre>
*/
l_int32
pixGetWordsInTextlines(PIX *pixs,
l_int32 minwidth,
l_int32 minheight,
l_int32 maxwidth,
l_int32 maxheight,
BOXA **pboxad,
PIXA **ppixad,
NUMA **pnai)
{
BOXA *boxa1, *boxad;
BOXAA *baa;
NUMA *nai;
NUMAA *naa;
PIXA *pixa1, *pixad;
PIXAA *paa;
PROCNAME("pixGetWordsInTextlines");
if (!pboxad || !ppixad || !pnai)
return ERROR_INT("&boxad, &pixad, &nai not all defined", procName, 1);
*pboxad = NULL;
*ppixad = NULL;
*pnai = NULL;
if (!pixs)
return ERROR_INT("pixs not defined", procName, 1);
/* Get the bounding boxes of the words from the word mask. */
pixWordBoxesByDilation(pixs, minwidth, minheight, maxwidth, maxheight,
&boxa1, NULL, NULL);
/* Generate a pixa of the word images */
pixa1 = pixaCreateFromBoxa(pixs, boxa1, NULL); /* mask over each word */
/* Sort the bounding boxes of these words by line. We use the
* index mapping to allow identical sorting of the pixa. */
baa = boxaSort2d(boxa1, &naa, -1, -1, 4);
paa = pixaSort2dByIndex(pixa1, naa, L_CLONE);
/* Flatten the word paa */
pixad = pixaaFlattenToPixa(paa, &nai, L_CLONE);
boxad = pixaGetBoxa(pixad, L_COPY);
*pnai = nai;
*pboxad = boxad;
*ppixad = pixad;
pixaDestroy(&pixa1);
boxaDestroy(&boxa1);
boxaaDestroy(&baa);
pixaaDestroy(&paa);
numaaDestroy(&naa);
return 0;
}
/*!
* \brief pixGetWordsInTextlines()
*
* \param[in] pixs 1 bpp, typ. 300 ppi
* \param[in] reduction 1 for input res; 2 for 2x reduction of input res
* \param[in] minwidth, minheight of saved components; smaller are discarded
* \param[in] maxwidth, maxheight of saved components; larger are discarded
* \param[out] pboxad word boxes sorted in textline line order
* \param[out] ppixad word images sorted in textline line order
* \param[out] pnai index of textline for each word
* \return 0 if OK, 1 on error
*
* <pre>
* Notes:
* (1) The input should be at a resolution of about 300 ppi.
* The word masks and word images can be computed at either
* 150 ppi or 300 ppi. For the former, set reduction = 2.
* (2) The four size constraints on saved components are all
* scaled by %reduction.
* (3) The result are word images (and their b.b.), extracted in
* textline order, at either full res or 2x reduction,
* and with a numa giving the textline index for each word.
* (4) The pixa and boxa interfaces should make this type of
* application simple to put together. The steps are:
* ~ optionally reduce by 2x
* ~ generate first estimate of word masks
* ~ get b.b. of these, and remove the small and big ones
* ~ extract pixa of the word images, using the b.b.
* ~ sort actual word images in textline order (2d)
* ~ flatten them to a pixa (1d), saving the textline index
* for each pix
* (5) In an actual application, it may be desirable to pre-filter
* the input image to remove large components, to extract
* single columns of text, and to deskew them. For example,
* to remove both large components and small noisy components
* that can interfere with the statistics used to estimate
* parameters for segmenting by words, but still retain text lines,
* the following image preprocessing can be done:
* Pix *pixt = pixMorphSequence(pixs, "c40.1", 0);
* Pix *pixf = pixSelectBySize(pixt, 0, 60, 8,
* L_SELECT_HEIGHT, L_SELECT_IF_LT, NULL);
* pixAnd(pixf, pixf, pixs); // the filtered image
* The closing turns text lines into long blobs, but does not
* significantly increase their height. But if there are many
* small connected components in a dense texture, this is likely
* to generate tall components that will be eliminated in pixf.
* </pre>
*/
l_int32
pixGetWordsInTextlines(PIX *pixs,
l_int32 reduction,
l_int32 minwidth,
l_int32 minheight,
l_int32 maxwidth,
l_int32 maxheight,
BOXA **pboxad,
PIXA **ppixad,
NUMA **pnai)
{
l_int32 maxdil;
BOXA *boxa1, *boxad;
BOXAA *baa;
NUMA *nai;
NUMAA *naa;
PIXA *pixa1, *pixad;
PIX *pix1;
PIXAA *paa;
PROCNAME("pixGetWordsInTextlines");
if (!pboxad || !ppixad || !pnai)
return ERROR_INT("&boxad, &pixad, &nai not all defined", procName, 1);
*pboxad = NULL;
*ppixad = NULL;
*pnai = NULL;
if (!pixs)
return ERROR_INT("pixs not defined", procName, 1);
if (reduction != 1 && reduction != 2)
return ERROR_INT("reduction not in {1,2}", procName, 1);
if (reduction == 1) {
pix1 = pixClone(pixs);
maxdil = 18;
} else { /* reduction == 2 */
pix1 = pixReduceRankBinaryCascade(pixs, 1, 0, 0, 0);
maxdil = 9;
}
/* Get the bounding boxes of the words from the word mask. */
pixWordBoxesByDilation(pix1, maxdil, minwidth, minheight,
maxwidth, maxheight, &boxa1, NULL);
/* Generate a pixa of the word images */
pixa1 = pixaCreateFromBoxa(pix1, boxa1, NULL); /* mask over each word */
/* Sort the bounding boxes of these words by line. We use the
* index mapping to allow identical sorting of the pixa. */
baa = boxaSort2d(boxa1, &naa, -1, -1, 4);
paa = pixaSort2dByIndex(pixa1, naa, L_CLONE);
/* Flatten the word paa */
pixad = pixaaFlattenToPixa(paa, &nai, L_CLONE);
boxad = pixaGetBoxa(pixad, L_COPY);
*pnai = nai;
*pboxad = boxad;
*ppixad = pixad;
pixDestroy(&pix1);
pixaDestroy(&pixa1);
boxaDestroy(&boxa1);
boxaaDestroy(&baa);
pixaaDestroy(&paa);
numaaDestroy(&naa);
return 0;
}