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      1 /*M///////////////////////////////////////////////////////////////////////////////////////
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      9 //
     10 //                        Intel License Agreement
     11 //                For Open Source Computer Vision Library
     12 //
     13 // Copyright (C) 2000, Intel Corporation, all rights reserved.
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     40 //M*/
     41 #include "_cv.h"
     42 
     43 #define _CV_ACOS_TABLE_SIZE  513
     44 
     45 static const float icv_acos_table[_CV_ACOS_TABLE_SIZE] = {
     46     3.14159265f, 3.05317551f, 3.01651113f, 2.98834964f, 2.96458497f, 2.94362719f,
     47     2.92466119f, 2.90720289f, 2.89093699f, 2.87564455f, 2.86116621f, 2.84738169f,
     48     2.83419760f, 2.82153967f, 2.80934770f, 2.79757211f, 2.78617145f, 2.77511069f,
     49     2.76435988f, 2.75389319f, 2.74368816f, 2.73372510f, 2.72398665f, 2.71445741f,
     50     2.70512362f, 2.69597298f, 2.68699438f, 2.67817778f, 2.66951407f, 2.66099493f,
     51     2.65261279f, 2.64436066f, 2.63623214f, 2.62822133f, 2.62032277f, 2.61253138f,
     52     2.60484248f, 2.59725167f, 2.58975488f, 2.58234828f, 2.57502832f, 2.56779164f,
     53     2.56063509f, 2.55355572f, 2.54655073f, 2.53961750f, 2.53275354f, 2.52595650f,
     54     2.51922417f, 2.51255441f, 2.50594525f, 2.49939476f, 2.49290115f, 2.48646269f,
     55     2.48007773f, 2.47374472f, 2.46746215f, 2.46122860f, 2.45504269f, 2.44890314f,
     56     2.44280867f, 2.43675809f, 2.43075025f, 2.42478404f, 2.41885841f, 2.41297232f,
     57     2.40712480f, 2.40131491f, 2.39554173f, 2.38980439f, 2.38410204f, 2.37843388f,
     58     2.37279910f, 2.36719697f, 2.36162673f, 2.35608768f, 2.35057914f, 2.34510044f,
     59     2.33965094f, 2.33423003f, 2.32883709f, 2.32347155f, 2.31813284f, 2.31282041f,
     60     2.30753373f, 2.30227228f, 2.29703556f, 2.29182309f, 2.28663439f, 2.28146900f,
     61     2.27632647f, 2.27120637f, 2.26610827f, 2.26103177f, 2.25597646f, 2.25094195f,
     62     2.24592786f, 2.24093382f, 2.23595946f, 2.23100444f, 2.22606842f, 2.22115104f,
     63     2.21625199f, 2.21137096f, 2.20650761f, 2.20166166f, 2.19683280f, 2.19202074f,
     64     2.18722520f, 2.18244590f, 2.17768257f, 2.17293493f, 2.16820274f, 2.16348574f,
     65     2.15878367f, 2.15409630f, 2.14942338f, 2.14476468f, 2.14011997f, 2.13548903f,
     66     2.13087163f, 2.12626757f, 2.12167662f, 2.11709859f, 2.11253326f, 2.10798044f,
     67     2.10343994f, 2.09891156f, 2.09439510f, 2.08989040f, 2.08539725f, 2.08091550f,
     68     2.07644495f, 2.07198545f, 2.06753681f, 2.06309887f, 2.05867147f, 2.05425445f,
     69     2.04984765f, 2.04545092f, 2.04106409f, 2.03668703f, 2.03231957f, 2.02796159f,
     70     2.02361292f, 2.01927344f, 2.01494300f, 2.01062146f, 2.00630870f, 2.00200457f,
     71     1.99770895f, 1.99342171f, 1.98914271f, 1.98487185f, 1.98060898f, 1.97635399f,
     72     1.97210676f, 1.96786718f, 1.96363511f, 1.95941046f, 1.95519310f, 1.95098292f,
     73     1.94677982f, 1.94258368f, 1.93839439f, 1.93421185f, 1.93003595f, 1.92586659f,
     74     1.92170367f, 1.91754708f, 1.91339673f, 1.90925250f, 1.90511432f, 1.90098208f,
     75     1.89685568f, 1.89273503f, 1.88862003f, 1.88451060f, 1.88040664f, 1.87630806f,
     76     1.87221477f, 1.86812668f, 1.86404371f, 1.85996577f, 1.85589277f, 1.85182462f,
     77     1.84776125f, 1.84370256f, 1.83964848f, 1.83559892f, 1.83155381f, 1.82751305f,
     78     1.82347658f, 1.81944431f, 1.81541617f, 1.81139207f, 1.80737194f, 1.80335570f,
     79     1.79934328f, 1.79533460f, 1.79132959f, 1.78732817f, 1.78333027f, 1.77933581f,
     80     1.77534473f, 1.77135695f, 1.76737240f, 1.76339101f, 1.75941271f, 1.75543743f,
     81     1.75146510f, 1.74749565f, 1.74352900f, 1.73956511f, 1.73560389f, 1.73164527f,
     82     1.72768920f, 1.72373560f, 1.71978441f, 1.71583556f, 1.71188899f, 1.70794462f,
     83     1.70400241f, 1.70006228f, 1.69612416f, 1.69218799f, 1.68825372f, 1.68432127f,
     84     1.68039058f, 1.67646160f, 1.67253424f, 1.66860847f, 1.66468420f, 1.66076139f,
     85     1.65683996f, 1.65291986f, 1.64900102f, 1.64508338f, 1.64116689f, 1.63725148f,
     86     1.63333709f, 1.62942366f, 1.62551112f, 1.62159943f, 1.61768851f, 1.61377831f,
     87     1.60986877f, 1.60595982f, 1.60205142f, 1.59814349f, 1.59423597f, 1.59032882f,
     88     1.58642196f, 1.58251535f, 1.57860891f, 1.57470259f, 1.57079633f, 1.56689007f,
     89     1.56298375f, 1.55907731f, 1.55517069f, 1.55126383f, 1.54735668f, 1.54344917f,
     90     1.53954124f, 1.53563283f, 1.53172389f, 1.52781434f, 1.52390414f, 1.51999323f,
     91     1.51608153f, 1.51216900f, 1.50825556f, 1.50434117f, 1.50042576f, 1.49650927f,
     92     1.49259163f, 1.48867280f, 1.48475270f, 1.48083127f, 1.47690845f, 1.47298419f,
     93     1.46905841f, 1.46513106f, 1.46120207f, 1.45727138f, 1.45333893f, 1.44940466f,
     94     1.44546850f, 1.44153038f, 1.43759024f, 1.43364803f, 1.42970367f, 1.42575709f,
     95     1.42180825f, 1.41785705f, 1.41390346f, 1.40994738f, 1.40598877f, 1.40202755f,
     96     1.39806365f, 1.39409701f, 1.39012756f, 1.38615522f, 1.38217994f, 1.37820164f,
     97     1.37422025f, 1.37023570f, 1.36624792f, 1.36225684f, 1.35826239f, 1.35426449f,
     98     1.35026307f, 1.34625805f, 1.34224937f, 1.33823695f, 1.33422072f, 1.33020059f,
     99     1.32617649f, 1.32214834f, 1.31811607f, 1.31407960f, 1.31003885f, 1.30599373f,
    100     1.30194417f, 1.29789009f, 1.29383141f, 1.28976803f, 1.28569989f, 1.28162688f,
    101     1.27754894f, 1.27346597f, 1.26937788f, 1.26528459f, 1.26118602f, 1.25708205f,
    102     1.25297262f, 1.24885763f, 1.24473698f, 1.24061058f, 1.23647833f, 1.23234015f,
    103     1.22819593f, 1.22404557f, 1.21988898f, 1.21572606f, 1.21155670f, 1.20738080f,
    104     1.20319826f, 1.19900898f, 1.19481283f, 1.19060973f, 1.18639955f, 1.18218219f,
    105     1.17795754f, 1.17372548f, 1.16948589f, 1.16523866f, 1.16098368f, 1.15672081f,
    106     1.15244994f, 1.14817095f, 1.14388370f, 1.13958808f, 1.13528396f, 1.13097119f,
    107     1.12664966f, 1.12231921f, 1.11797973f, 1.11363107f, 1.10927308f, 1.10490563f,
    108     1.10052856f, 1.09614174f, 1.09174500f, 1.08733820f, 1.08292118f, 1.07849378f,
    109     1.07405585f, 1.06960721f, 1.06514770f, 1.06067715f, 1.05619540f, 1.05170226f,
    110     1.04719755f, 1.04268110f, 1.03815271f, 1.03361221f, 1.02905939f, 1.02449407f,
    111     1.01991603f, 1.01532509f, 1.01072102f, 1.00610363f, 1.00147268f, 0.99682798f,
    112     0.99216928f, 0.98749636f, 0.98280898f, 0.97810691f, 0.97338991f, 0.96865772f,
    113     0.96391009f, 0.95914675f, 0.95436745f, 0.94957191f, 0.94475985f, 0.93993099f,
    114     0.93508504f, 0.93022170f, 0.92534066f, 0.92044161f, 0.91552424f, 0.91058821f,
    115     0.90563319f, 0.90065884f, 0.89566479f, 0.89065070f, 0.88561619f, 0.88056088f,
    116     0.87548438f, 0.87038629f, 0.86526619f, 0.86012366f, 0.85495827f, 0.84976956f,
    117     0.84455709f, 0.83932037f, 0.83405893f, 0.82877225f, 0.82345981f, 0.81812110f,
    118     0.81275556f, 0.80736262f, 0.80194171f, 0.79649221f, 0.79101352f, 0.78550497f,
    119     0.77996593f, 0.77439569f, 0.76879355f, 0.76315878f, 0.75749061f, 0.75178826f,
    120     0.74605092f, 0.74027775f, 0.73446785f, 0.72862033f, 0.72273425f, 0.71680861f,
    121     0.71084240f, 0.70483456f, 0.69878398f, 0.69268952f, 0.68654996f, 0.68036406f,
    122     0.67413051f, 0.66784794f, 0.66151492f, 0.65512997f, 0.64869151f, 0.64219789f,
    123     0.63564741f, 0.62903824f, 0.62236849f, 0.61563615f, 0.60883911f, 0.60197515f,
    124     0.59504192f, 0.58803694f, 0.58095756f, 0.57380101f, 0.56656433f, 0.55924437f,
    125     0.55183778f, 0.54434099f, 0.53675018f, 0.52906127f, 0.52126988f, 0.51337132f,
    126     0.50536051f, 0.49723200f, 0.48897987f, 0.48059772f, 0.47207859f, 0.46341487f,
    127     0.45459827f, 0.44561967f, 0.43646903f, 0.42713525f, 0.41760600f, 0.40786755f,
    128     0.39790449f, 0.38769946f, 0.37723277f, 0.36648196f, 0.35542120f, 0.34402054f,
    129     0.33224495f, 0.32005298f, 0.30739505f, 0.29421096f, 0.28042645f, 0.26594810f,
    130     0.25065566f, 0.23438976f, 0.21693146f, 0.19796546f, 0.17700769f, 0.15324301f,
    131     0.12508152f, 0.08841715f, 0.00000000f
    132 };
    133 
    134 
    135 /*F///////////////////////////////////////////////////////////////////////////////////////
    136 //    Name: icvCalcPGH
    137 //    Purpose:
    138 //      Calculates PGH(pairwise geometric histogram) for contour given.
    139 //    Context:
    140 //    Parameters:
    141 //      contour  - pointer to input contour object.
    142 //      pgh      - output histogram
    143 //      ang_dim  - number of angle bins (vertical size of histogram)
    144 //      dist_dim - number of distance bins (horizontal size of histogram)
    145 //    Returns:
    146 //      CV_OK or error code
    147 //    Notes:
    148 //F*/
    149 static CvStatus
    150 icvCalcPGH( const CvSeq * contour, float *pgh, int angle_dim, int dist_dim )
    151 {
    152     char local_buffer[(1 << 14) + 32];
    153     float *local_buffer_ptr = (float *)cvAlignPtr(local_buffer,32);
    154     float *buffer = local_buffer_ptr;
    155     double angle_scale = (angle_dim - 0.51) / icv_acos_table[0];
    156     double dist_scale = DBL_EPSILON;
    157     int buffer_size;
    158     int i, count, pass;
    159     int *pghi = (int *) pgh;
    160     int hist_size = angle_dim * dist_dim;
    161     CvSeqReader reader1, reader2;       /* external and internal readers */
    162 
    163     if( !contour || !pgh )
    164         return CV_NULLPTR_ERR;
    165 
    166     if( angle_dim <= 0 || angle_dim > 180 || dist_dim <= 0 )
    167         return CV_BADRANGE_ERR;
    168 
    169     if( !CV_IS_SEQ_POLYGON( contour ))
    170         return CV_BADFLAG_ERR;
    171 
    172     memset( pgh, 0, hist_size * sizeof( pgh[0] ));
    173 
    174     count = contour->total;
    175 
    176     /* allocate buffer for distances */
    177     buffer_size = count * sizeof( float );
    178 
    179     if( buffer_size > (int)sizeof(local_buffer) - 32 )
    180     {
    181         buffer = (float *) cvAlloc( buffer_size );
    182         if( !buffer )
    183             return CV_OUTOFMEM_ERR;
    184     }
    185 
    186     cvStartReadSeq( contour, &reader1, 0 );
    187     cvStartReadSeq( contour, &reader2, 0 );
    188 
    189     /* calc & store squared edge lengths, calculate maximal distance between edges */
    190     for( i = 0; i < count; i++ )
    191     {
    192         CvPoint pt1, pt2;
    193         double dx, dy;
    194 
    195         CV_READ_EDGE( pt1, pt2, reader1 );
    196 
    197         dx = pt2.x - pt1.x;
    198         dy = pt2.y - pt1.y;
    199         buffer[i] = (float)(1./sqrt(dx * dx + dy * dy));
    200     }
    201 
    202     /*
    203        do 2 passes.
    204        First calculates maximal distance.
    205        Second calculates histogram itself.
    206      */
    207     for( pass = 1; pass <= 2; pass++ )
    208     {
    209         double dist_coeff = 0, angle_coeff = 0;
    210 
    211         /* run external loop */
    212         for( i = 0; i < count; i++ )
    213         {
    214             CvPoint pt1, pt2;
    215             int dx, dy;
    216             int dist = 0;
    217 
    218             CV_READ_EDGE( pt1, pt2, reader1 );
    219 
    220             dx = pt2.x - pt1.x;
    221             dy = pt2.y - pt1.y;
    222 
    223             if( (dx | dy) != 0 )
    224             {
    225                 int j;
    226 
    227                 if( pass == 2 )
    228                 {
    229                     dist_coeff = buffer[i] * dist_scale;
    230                     angle_coeff = buffer[i] * (_CV_ACOS_TABLE_SIZE / 2);
    231                 }
    232 
    233                 /* run internal loop (for current edge) */
    234                 for( j = 0; j < count; j++ )
    235                 {
    236                     CvPoint pt3, pt4;
    237 
    238                     CV_READ_EDGE( pt3, pt4, reader2 );
    239 
    240                     if( i != j )        /* process edge pair */
    241                     {
    242                         int d1 = (pt3.y - pt1.y) * dx - (pt3.x - pt1.x) * dy;
    243                         int d2 = (pt4.y - pt1.y) * dx - (pt2.x - pt1.x) * dy;
    244                         int cross_flag;
    245                         int *hist_row = 0;
    246 
    247                         if( pass == 2 )
    248                         {
    249                             int dp = (pt4.x - pt3.x) * dx + (pt4.y - pt3.y) * dy;
    250 
    251                             dp = cvRound( dp * angle_coeff * buffer[j] ) +
    252                                 (_CV_ACOS_TABLE_SIZE / 2);
    253                             dp = MAX( dp, 0 );
    254                             dp = MIN( dp, _CV_ACOS_TABLE_SIZE - 1 );
    255                             hist_row = pghi + dist_dim *
    256                                 cvRound( icv_acos_table[dp] * angle_scale );
    257 
    258                             d1 = cvRound( d1 * dist_coeff );
    259                             d2 = cvRound( d2 * dist_coeff );
    260                         }
    261 
    262                         cross_flag = (d1 ^ d2) < 0;
    263 
    264                         d1 = CV_IABS( d1 );
    265                         d2 = CV_IABS( d2 );
    266 
    267                         if( pass == 2 )
    268                         {
    269                             if( d1 >= dist_dim )
    270                                 d1 = dist_dim - 1;
    271                             if( d2 >= dist_dim )
    272                                 d2 = dist_dim - 1;
    273 
    274                             if( !cross_flag )
    275                             {
    276                                 if( d1 > d2 )   /* make d1 <= d2 */
    277                                 {
    278                                     d1 ^= d2;
    279                                     d2 ^= d1;
    280                                     d1 ^= d2;
    281                                 }
    282 
    283                                 for( ; d1 <= d2; d1++ )
    284                                     hist_row[d1]++;
    285                             }
    286                             else
    287                             {
    288                                 for( ; d1 >= 0; d1-- )
    289                                     hist_row[d1]++;
    290                                 for( ; d2 >= 0; d2-- )
    291                                     hist_row[d2]++;
    292                             }
    293                         }
    294                         else    /* 1st pass */
    295                         {
    296                             d1 = CV_IMAX( d1, d2 );
    297                             dist = CV_IMAX( dist, d1 );
    298                         }
    299                     }           /* end of processing of edge pair */
    300 
    301                 }               /* end of internal loop */
    302 
    303                 if( pass == 1 )
    304                 {
    305                     double scale = dist * buffer[i];
    306 
    307                     dist_scale = MAX( dist_scale, scale );
    308                 }
    309             }
    310         }                       /* end of external loop */
    311 
    312         if( pass == 1 )
    313         {
    314             dist_scale = (dist_dim - 0.51) / dist_scale;
    315         }
    316 
    317     }                           /* end of pass on loops */
    318 
    319 
    320     /* convert hist to floats */
    321     for( i = 0; i < hist_size; i++ )
    322     {
    323         ((float *) pghi)[i] = (float) pghi[i];
    324     }
    325 
    326     if( buffer != local_buffer_ptr )
    327         cvFree( &buffer );
    328 
    329     return CV_OK;
    330 }
    331 
    332 
    333 CV_IMPL void
    334 cvCalcPGH( const CvSeq * contour, CvHistogram * hist )
    335 {
    336     CV_FUNCNAME( "cvCalcPGH" );
    337 
    338     __BEGIN__;
    339 
    340     int size[CV_MAX_DIM];
    341     int dims;
    342 
    343     if( !CV_IS_HIST(hist))
    344         CV_ERROR( CV_StsBadArg, "The histogram header is invalid " );
    345 
    346     if( CV_IS_SPARSE_HIST( hist ))
    347         CV_ERROR( CV_StsUnsupportedFormat, "Sparse histogram are not supported" );
    348 
    349     dims = cvGetDims( hist->bins, size );
    350 
    351     if( dims != 2 )
    352         CV_ERROR( CV_StsBadSize, "The histogram must be two-dimensional" );
    353 
    354     if( !CV_IS_SEQ_POLYGON( contour ) || CV_SEQ_ELTYPE( contour ) != CV_32SC2 )
    355         CV_ERROR( CV_StsUnsupportedFormat, "The contour is not valid or the point type is not supported" );
    356 
    357     IPPI_CALL( icvCalcPGH( contour, ((CvMatND*)(hist->bins))->data.fl, size[0], size[1] ));
    358 
    359     __END__;
    360 }
    361 
    362 
    363 /* End of file. */
    364