the following are patch 81 and 82.

remove some spacing problems in my last patch,
change t_y into k, negative math hurts my head.
added a memset() call i missed the chance to last time,
reversed conv[]'s order in memory...
swapped X and Y in the image stored in conv[], so as to sequentialize memory 
accesses.

gift 0.0.15a performs a gabor filter on an image once every two seconds.
once these patches are committed, the CVS version will perform a gabor filter 
on an image every second.
100% faster, new and improved! :)

my personal tree contains another 20% speed boost (down to 0.8 seconds per 
image).

this is all measured on a P4M 2.2Ghz machine.

i like accomplishing things. :)

Julia Longtin <[EMAIL PROTECTED]>
--- ../../dev2/gift/ChangeLog   2006-09-20 16:42:51.000000000 +0000
+++ ChangeLog   2006-09-20 20:55:52.000000000 +0000
@@ -1,3 +1,10 @@
+2006-09-20    <[EMAIL PROTECTED]>
+
+       * FeatureExtraction/gabor.c
+       use one more memset.
+       reverse order of conv[] in memory.
+       swap conv[]'s x and y axis, to use in-order memory accesses.
+
 2006-09-19    <[EMAIL PROTECTED]>
 
        * FeatureExtraction/gabor.c
--- ../../dev2/gift/FeatureExtraction/gabor.c   2006-09-20 16:42:51.000000000 
+0000
+++ FeatureExtraction/gabor.c   2006-09-20 20:50:33.000000000 +0000
@@ -93,10 +93,10 @@
        double conv[MAX_WIDTH*MAX_HEIGHT]; /* take advantage of our fixed image 
size. */
        double * target_conv;
        double * target_image;
-        double temparray[kernal_size[2]];
+       double temparray[kernal_size[2]];
 
-       memset(&conv, 0, MAX_WIDTH*MAX_HEIGHT*sizeof(double)); 
-       memset(output, 0, MAX_WIDTH*MAX_HEIGHT*sizeof(double)); 
+       memset(&conv, 0, MAX_WIDTH*MAX_HEIGHT*sizeof(double));
+       memset(output, 0, MAX_WIDTH*MAX_HEIGHT*sizeof(double));
 
        /* first convolution */
        target_kernal=kernelsxy[filter_scale*num_gabors_per_scale+orientation];
@@ -108,13 +108,13 @@
                    for (k = 0; k < kernal_size[filter_scale]; k++)
                      temparray[k]= target_kernal[k]*target_image[k];
                    for (k = 0; k < kernal_size[filter_scale]; k++)
-                     conv[y*width+x] += temparray[k];
+                     conv[((width*height)-1)-(x*height+y)] += temparray[k];
                  }
                else
                  {
                for (k=0; k < kernal_size[filter_scale]; k++) {
                        if ((x+kernal_size[filter_scale]/2 >= k) && 
(x+kernal_size[filter_scale]/2 < width+k)) {
-                               conv[y*width + x] +=
+                               conv[((width*height)-1)-(x*height+y)] +=
                                        target_kernal[k]*target_image[k];
                        }
                }
@@ -129,13 +129,12 @@
                for (t_y = -kernal_size[filter_scale]/2; t_y <= 
kernal_size[filter_scale]/2; t_y++) {
                        if (((y - t_y) >= 0) && ((y - t_y) < height))
                                output[y*width + x] +=
-                                       target_kernal[t_y + 
kernal_size[filter_scale]/2]*conv[(y - t_y)*width + x];
+                                       target_kernal[t_y + 
kernal_size[filter_scale]/2]*conv[((width*height)-1)-(x*height+(y - t_y))];
                }
        }
        }
 
-       for (i = 0; i < width*height; i++)
-               conv[i] = 0;
+       memset(&conv, 0, MAX_WIDTH*MAX_HEIGHT*sizeof(double));
 
        /* third convolution */
        target_kernal=&target_kernal[kernal_size[filter_scale]];
@@ -147,13 +146,13 @@
                    for (k = 0; k < kernal_size[filter_scale]; k++)
                      temparray[k]= target_kernal[k]*target_image[k];
                    for (k = 0; k < kernal_size[filter_scale]; k++)
-                     conv[y*width+x] += temparray[k];
+                     conv[((width*height)-1)-(x*height+y)] += temparray[k];
                  }
                else
                  {
                for (k=0; k < kernal_size[filter_scale]; k++) {
                        if ((x+kernal_size[filter_scale]/2 >= k) && 
(x+kernal_size[filter_scale]/2 < width+k)) {
-                               conv[y*width + x] +=
+                               conv[((width*height)-1)-(x*height+y)] +=
                                        target_kernal[k]*target_image[k];
                        }
                }
@@ -168,7 +167,7 @@
                for (t_y = -kernal_size[filter_scale]/2; t_y <= 
kernal_size[filter_scale]/2; t_y++) {
                        if (((y - t_y) >= 0) && ((y - t_y) < height))
                                output[y*width + x] -=
-                                       target_kernal[t_y + 
kernal_size[filter_scale]/2]*conv[(y - t_y)*width + x];
+                                       target_kernal[t_y + 
kernal_size[filter_scale]/2]*conv[((width*height)-1)-(x*height+(y - t_y))];
                }
        }
        }
--- ../../dev/gift/ChangeLog    2006-09-20 20:55:52.000000000 +0000
+++ ChangeLog   2006-09-20 21:33:38.000000000 +0000
@@ -1,6 +1,11 @@
 2006-09-20    <[EMAIL PROTECTED]>
 
        * FeatureExtraction/gabor.c
+       replace t_y with k. remove t_y and i, no longer in use.
+
+2006-09-20    <[EMAIL PROTECTED]>
+
+       * FeatureExtraction/gabor.c
        use one more memset.
        reverse order of conv[] in memory.
        swap conv[]'s x and y axis, to use in-order memory accesses.
--- ../../dev/gift/FeatureExtraction/gabor.c    2006-09-20 20:50:33.000000000 
+0000
+++ FeatureExtraction/gabor.c   2006-09-20 21:30:58.000000000 +0000
@@ -86,8 +86,6 @@
 void gabor_filter(double *image, int width, int height, int filter_scale, int 
orientation, double **kernelsxy, double *output) {
 
        uint32_t x, y;
-       int32_t t_y;
-       uint32_t i;
        uint32_t k;
        double * target_kernal;
        double conv[MAX_WIDTH*MAX_HEIGHT]; /* take advantage of our fixed image 
size. */
@@ -126,10 +124,11 @@
        target_kernal=&target_kernal[kernal_size[filter_scale]];
        for (x = 0; x < width; x++) {
        for (y = 0; y < height; y++) {
-               for (t_y = -kernal_size[filter_scale]/2; t_y <= 
kernal_size[filter_scale]/2; t_y++) {
-                       if (((y - t_y) >= 0) && ((y - t_y) < height))
+               
target_conv=&conv[((width*height)-1)-(x*height+y+(kernal_size[filter_scale]/2))];
+               for (k = 0; k < kernal_size[filter_scale]; k++) {
+                       if (((y+(kernal_size[filter_scale]/2))>=k) && 
(y+(kernal_size[filter_scale]/2)<height+k))
                                output[y*width + x] +=
-                                       target_kernal[t_y + 
kernal_size[filter_scale]/2]*conv[((width*height)-1)-(x*height+(y - t_y))];
+                                       target_kernal[k]*target_conv[k];
                }
        }
        }
@@ -164,10 +163,11 @@
        target_kernal=&target_kernal[kernal_size[filter_scale]];
        for (x = 0; x < width; x++) {
        for (y = 0; y < height; y++) {
-               for (t_y = -kernal_size[filter_scale]/2; t_y <= 
kernal_size[filter_scale]/2; t_y++) {
-                       if (((y - t_y) >= 0) && ((y - t_y) < height))
+               
target_conv=&conv[((width*height)-1)-(x*height+y+(kernal_size[filter_scale]/2))];
+               for (k = 0; k < kernal_size[filter_scale]; k++) {
+                       if (((y+(kernal_size[filter_scale]/2))>=k) && 
(y+(kernal_size[filter_scale]/2)<height+k))
                                output[y*width + x] -=
-                                       target_kernal[t_y + 
kernal_size[filter_scale]/2]*conv[((width*height)-1)-(x*height+(y - t_y))];
+                                       target_kernal[k]*target_conv[k];
                }
        }
        }
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