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16 Chapter 1 ■ Practical Aspects of a Vision System

img = newimage (x->height, x->width);
else if ((x->depth==8) && (x->nChannels==3)) //Color
{
color = 1;
img = newimage (x->height, x->width);
}
else return 0;

for (i=0; i<x->height; i++)
{
for (j=0; j<x->width; j++)
{
s = cvGet2D (x, i, j);
if (color)
k= (unsigned char) ((s.val[0]+s.val[1]+s.val[2])/3);
else k = (unsigned char)(s.val[0]);
img->data[i][j] = k;
}
}
return img;
}

The two functions toOpenCV and fromOpenCV do the job of allowing the
image-processing routines developed here to be used with OpenCV. As a
demonstration, here is the main routine only for a program that thresholds
an image using the method of grey-level histograms devised by Otsu and
presented in Chapter 4. It is very much like the program for thresholding
written earlier in Section 1.2.4, but instead uses the AIPCV library function
thr_glh to find the threshold and apply it.

int main(int argc, char *argv[])
{
IplImage* img=0;
IplImage* img2=0;
IMAGE x;
int height,width,step,channels;
uchar *data;
int mean=0,count=0;

if(argc<1){
printf(“Usage: main <image-file-name>\n\7“);
exit(0);
}
// load an image
img=cvLoadImage(“H:/AIPCV/marchA062.jpg“);