mmdConcrete
Aggregate and anhydrous phase extraction from a concrete section observed by a SEM image.

The SEM image of a polished concrete section is read. The anhydrous phase are the white pores, while the aggregate are the medium-gray homogeneous pores.

Image f = mmReadgray("csample.jpg");
mmShow(f);

f

The histogram has a small peak in the white region related to the anhydrous phase.

Image h = mmHistogram(f);
mmPlot(h);

h

The threshold value is extracted using the watershed technique. The aim is to detect the middle valley of the histogram. If the histogram is negated, we need to extract the middle peak of the 1D signal. This is accomplished by find proper markers on the valleys. These markers are extracted by detecting the regional minima of the filtered signal (alternating sequential filtering, closing followed by opening of length 5 pixels). To discard the detection of peaks near the limits of the histogram, an intersection is done using the mmFrame function. For illustrative purpose, a plot of all the signals involved is displayed.

Image hf  = mmAsf(mmNeg(h), "co", mmSeline(5));
Image ws  = mmWatershed(hf);
Image wsf = mmIntersec(mmNeg(mmFrame(ws, 20, 0, 0, 1, 0)), ws);
//
CvPoint pmax;
IplImage *wsf_ipl = (IplImage *)wsf;
cvMinMaxLoc(wsf_ipl, 0, 0, 0, &pmax);
cvReleaseImage(&wsf_ipl);
int t = pmax.x;
printf("t = %d\n", t);
//
int mmax = mmStats(h, "max");
Image hf_plot  = mmNeg(hf);
Image ws_plot  = mmGray(ws, "uint16", mmax);
Image wsf_plot = mmGray(wsf, "uint16", mmax);
Image the_plot = mmConcat("H", hf_plot, ws_plot, wsf_plot);
mmPlot(the_plot);

t = 186

the_plot

The threshold value found in the previous step is applied. After, a filter to remove blobs smaller then 20 pixels is applied. For illustrative, the contour of the anhydrous grains are displayed as an overlay on the original image.

Image aux = mmThreshad(f, t, 255);
Image anidro = mmAreaopen(aux, 20);
mmShow( f, mmGradm(anidro));

f, mmGradm(anidro)

The watershed applied on the gradient using the markers from filtered regional minima of the gradient is a standard watershed based technique. In this case the filter was chosen to be a contrast mmHmin .

Image g  = mmGradm(f);
Image m  = mmRegmin(mmHmin(g, 10));
ws       = mmCwatershed(g, m);
mmShow(ws);

ws

The result of the watershed in the previous step is the detection of a large number of regions. The larger ones are the aggregate and the anhydrous. So first the regions are filtered out using an area criterion of 300 pixels. Small holes (area <= 50) are closed. The aggregate is obtained by removing the anhydrous phase.

Image aux1 = mmAreaopen(mmNeg(ws), 300);
Image aux2 = mmAreaclose(aux1, 50);
Image aggr = mmSubm(aux2, anidro);
mmShow(f, mmGradm(aggr));

f, mmGradm(aggr)

Finally each phase is measured and an illustrative display is constructed. The grains contoured by red are the aggregate and those contoured by green, the anhydrous.

int n = f.width()*f.height()*f.depth();
double anidro_phase = (double)mmStats(anidro, "sum")/n;
double aggr_phase   = (double)mmStats(aggr,   "sum")/n;
printf("anidro = %f\n", anidro_phase);
printf("aggr   = %f\n", aggr_phase);
mmShow( f, mmGradm(aggr), mmGradm(anidro));

anidro = 0.114593
aggr   = 0.252002

f, mmGradm(aggr), mmGradm(anidro)