Hough Transform

Edge detection, i think, is one of the imp steps of any shape detection algo. 

there are no specific shape extraction algorithms as such. but you can use edge detection techniques for finding the edges and depending the specific shape you want, you should write the logic in MATLAB. of course there are inbuilt shape detection algorithms in MATLAB, for example, you can detect the circle shapes in MATLAB 2013 using the following code:

I = imread('coins.png'); % read the image

hautoth = vision.Autothresholder;

BW = step(hautoth, I); % threshold the image

[y, x]= find(BW,1); % select a starting point for the trace

% Determine the boundaries

hboundtrace = vision.BoundaryTracer;

PTS = step(hboundtrace, BW, [x y]);

% Display the results

figure, imshow(BW);

hold on; plot(PTS(:,1), PTS(:,2), 'r', 'Linewidth',2);

hold on; plot(x,y,'gx','Linewidth',2); % show the starting point.

the result you get is:

file attached .

thank you sir.

 I think you can try all edge detection operators like sobel and Canny etc. You can also try different wavelets like curvelets and dual tree complex wavelet transforms.

Check out this paper:" Shape Matching and Object Recognition using Low Distortion Correspondence".

Shape feature algorithm

http://www.mecs-press.org/ijieeb/ijieeb-v8-n4/IJIEEB-V8-N4-8.pdf

for my spectral work image data extraction and analysis,  i had developed simple tool, Graphixy

Link: https://sourceforge.net/projects/graphixy/