mmdpieces - Classify two dimensional pieces.

Description

The input image is a binary image typically found in industrial automation applications. It has three types of objects: rings, nails and T-pins. Our procedure for identification of these classes of objects is based on thickening, thinning and reconstruction.

Reading

The binary image of the pieces is read.

a = mmreadgray('pieces_bw.tif'); mmshow(a); (a)

Contour noise reduction

An homotopic thickening is applied to reduce contour noise.

seA = mmimg2se(mmbinary(uint8([0 1 0;1 0 1;0 0 0]))); seB = mmimg2se(mmbinary(uint8([1 1 1;1 0 1;1 1 1]))); iAB = mmse2interval(seA,seB); mmintershow(iAB) ans = . 1 . 1 0 1 . . . b = mmthick(a, iAB); mmshow(b); (b)

Skeleton

The homotopic skeleton by thinning is created.

c = mmthin(b); mmshow(c); (c)

Skeleton pruning

The open lines of the skeleton are pruned by the end point thinning. The remaining skeleton components will be loops, identifying the rings.

d = mmthin(c,mmendpoints); mmshow(c,d); (c,d)

Detect rings

Extraction of the rings by reconstruction of the thicked image from the filtered skeleton.

e = mminfrec(d,b); mmshow(e); (e)

Rings in the input image

Restriction of the objects detected to the input-image.

f = mmintersec(a,e); mmshow(f); (f)

Skeleton of the remaining objects

It eliminates the skeleton of the rings.

g = mmsubm(c,e); mmshow(g); (g)

End points filtering

It removes sucessively 4 end-points to let T junctions just on T-pins.

h = mmthin(g, mmendpoints, 4); mmshow(h); (h)

T-pins markers

It detects triple points, applying the union of matchings with two templates. These points will identify (mark) the T-pins.

seA1 = mmimg2se(mmbinary(uint8([0 1 0; 0 1 0; 1 0 1]))); seB1 = mmimg2se(mmbinary(uint8([1 1 1; 0 1 0; 1 0 1]))); seA2 = mmimg2se(mmbinary(uint8([0 1 0; 1 1 1; 0 0 0]))); seB2 = mmimg2se(mmbinary(uint8([0 1 0; 1 1 1; 1 0 1]))); i1 = mmsupcanon(h, mmse2interval(seA1,seB1)); i2 = mmsupcanon(h, mmse2interval(seA2,seB2)); i = mmunion(i1,i2); mmshow(h,mmdil(i,mmsedisk(2))); (h,mmdil(i,mmsedisk(2)))

Detect T-pins

Detection of the T-pins by reconstruction of the ticked image from the T-pin markers.

j = mminfrec(i,b,mmsebox); mmshow(j); (j)

T-pins in the input image

Restriction of the objects detect to the input image

k = mmintersec(a,j); mmshow(k); (k)

Detect nails

The nails are imediatly detected by the subtration of the images of the rings and T-pints from the input image.

l = mmsubm(mmsubm(a,f),k); mmshow(l); (l)

Color composition

The result of the classification is presented in a pseudo color image.

m = mmgray(f,'uint8',1); n = mmgray(k,'uint8',2); o = mmgray(l,'uint8',3); p = mmunion(m,n,o); mmlblshow(p); (p)

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