/*!
 * \brief   pixGetWordBoxesInTextlines()
 *
 * \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]   pnai [optional] 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 can be computed at either 150 ppi or 300 ppi.
 *          For the former, set reduction = 2.
 *      (2) This is a special version of pixGetWordsInTextlines(), that
 *          just finds the word boxes in line order, with a numa
 *          giving the textline index for each word.
 *          See pixGetWordsInTextlines() for more details.
 * </pre>
 */
l_int32
pixGetWordBoxesInTextlines(PIX     *pixs,
                           l_int32  reduction,
                           l_int32  minwidth,
                           l_int32  minheight,
                           l_int32  maxwidth,
                           l_int32  maxheight,
                           BOXA   **pboxad,
                           NUMA   **pnai)
{
l_int32  maxdil;
BOXA    *boxa1;
BOXAA   *baa;
NUMA    *nai;
PIX     *pix1;

    PROCNAME("pixGetWordBoxesInTextlines");

    if (pnai) *pnai = NULL;
    if (!pboxad)
        return ERROR_INT("&boxad and &nai not both defined", procName, 1);
    *pboxad = 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);

        /* 2D sort the bounding boxes of these words. */
    baa = boxaSort2d(boxa1, NULL, 3, -5, 5);

        /* Flatten the boxaa, saving the boxa index for each box */
    *pboxad = boxaaFlattenToBoxa(baa, &nai, L_CLONE);

    if (pnai)
        *pnai = nai;
    else
        numaDestroy(&nai);
    pixDestroy(&pix1);
    boxaDestroy(&boxa1);
    boxaaDestroy(&baa);
    return 0;
}
示例#2
0
/*!
 * \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;
}
示例#3
0
/*!
 * \brief   pixGetWordBoxesInTextlines()
 *
 * \param[in]    pixs 1 bpp, typ. 300 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]   pnai [optional] 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) This is a special version of pixGetWordsInTextlines(), that
 *          just finds the word boxes in line order, with a numa
 *          giving the textline index for each word.
 *          See pixGetWordsInTextlines() for more details.
 * </pre>
 */
l_int32
pixGetWordBoxesInTextlines(PIX     *pixs,
                           l_int32  minwidth,
                           l_int32  minheight,
                           l_int32  maxwidth,
                           l_int32  maxheight,
                           BOXA   **pboxad,
                           NUMA   **pnai)
{
BOXA    *boxa1;
BOXAA   *baa;
NUMA    *nai;

    PROCNAME("pixGetWordBoxesInTextlines");

    if (pnai) *pnai = NULL;
    if (!pboxad)
        return ERROR_INT("&boxad and &nai not both defined", procName, 1);
    *pboxad = 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);

        /* 2D sort the bounding boxes of these words. */
    baa = boxaSort2d(boxa1, NULL, 3, -5, 5);

        /* Flatten the boxaa, saving the boxa index for each box */
    *pboxad = boxaaFlattenToBoxa(baa, &nai, L_CLONE);

    if (pnai)
        *pnai = nai;
    else
        numaDestroy(&nai);
    boxaDestroy(&boxa1);
    boxaaDestroy(&baa);
    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;
}