MATLAB: Error in the Code , it didnt produce correct result

doit4meImage Processing Toolboximage segmentationno attempt

If i've an image like : http://img836.imageshack.us/img836/6417/1zw.gif How can i identify the major two arcs in that image .

If the arcs can be modeled by y=(ax)^1/2 +b where a and b are constants such that a∈[250,400] and b∈[0,50] where b is an integer number as it represents the y-intercept of the arc in the image.

Output should be a 2-pixel thicker version of the detected arcs over the original image

May this will done by Hough Transform

Any Demo for doing that !please

Best Answer

Just filter out the grid points - they seem to be at fixed positions so it will be very easy to find them but just summing vertically and horizontally and look for high sums

verticalProfile = sum(grayImage, 2);
horizontalProfile = sum(grayImage, 1);
gridLocations = verticalProfile > 50; % or whatever.
grayImage(gridLocations, :) = 0; % Make those rows black.

etc. doing the same for the vertical grid lines.....

Then you have just the curves. Find each one and use polyfit() or whatever.

Related Solutions

MATLAB: How Can I recognize/detect the Needle/hand in the below images

ImageAnalyst will certainly provide a fancy solution (like a bwGetBlobAngle from his FEX ;-)), but (waiting for him to hit the forum) here is one way to do it "by hand" (I did that during a short pause, so all should be optimized).

=== VERSION 07/31, 2 =======================================================

Reading another post by ImageAnalyst, I realize that I should learn more about NORMXCORR2, but here is a version based on a 2D convolution for matching the "200" in the indicator. I chose it because it should never be hidden by the needle. From the center of the match, we get the center of rotation of the needle by adding a fixed offset. I generated a shifted 3rd image to test the approach. I attached the shifted image, the code and a template file (for the match) to this answer, below.

 clear ;  close all ;  clc ;
 display      = true ;             % True for debug, false for processing
                                   %   large number of files.
 % - Parameters associated with the needle
 originAngle  = 4 ;                % Used to compensate for the image tilt.
 needleLength = 400 ;
 % - Parameters associated with the curve around the needle center.
 curveRadius  = 200 ;
 kernelSize   = 30 ;               % Kernel size for 1D conv along curve.
 % - Parameters associated with the window that must frame the "200"
 %  on the indicator.
 w200Center   = [1000, 1860] ;     % Approx. center of window "200".
 w200OffsetNC = [290, 180] ;       % Approx. offset to needle center.
 w200width    = 800 ;
 w200Height   = 600 ;
 w200MatFile  = 'w200_threshold08_template.mat' ;
 % - Load/build '200' template for 2D convolution. Prepare for convolution
 %  purpose: remap 0 to -1 and 1 to 1.
 loaded        = load( w200MatFile ) ;
 w200Template = -1 + 2 * rot90( double( loaded.thresh08_200 ), 2 ) ;
 % - Get listing of jpeg files.
 D_jpg  = dir( '*.jpg' ) ;
 nFiles = numel( D_jpg ) ;
 % - Prealloc(s), initialize.
 needleAngles = zeros( nFiles, 1 ) ;
 w200RowBnd   = round( w200Center(1) + 0.5*[-w200Height, w200Height] ) ;
 w200ColBnd   = round( w200Center(2) + 0.5*[-w200width, w200width] ) ;
 for fId = 1 : nFiles
    % Initialize angle with NaN (=failed).
    needleAngles(fId) = NaN ;
    % - Read and "flatten" image.
    I_flat = sum( imread( D_jpg(fId).name ), 3 ) ;
    tic ;
    % - Extract window "200", threshold @ 80% for comparison with template.
    w200 = I_flat(w200RowBnd(1):w200RowBnd(2), w200ColBnd(1):w200ColBnd(2)) ;
    w200 = w200 > 0.8 * max( w200(:) ) ;
    % - Match template in window.
    match = conv2( double( w200 ), w200Template, 'same' ) ;
    [r, c] = find( match == max( match(:) ) ) ;
    if numel( r ) > 1
        fprintf( '%-20s: failed to match "200" template.\n', D_jpg(fId).name ) ;
        if ~display
            continue ;  % Loop back, leaving NaN angle value.
        end
    end
    matchCenter(1) = r(1) ;
    matchCenter(2) = c(1) ;
    % - Compute needle center.
    needleCenter = [w200RowBnd(1) + matchCenter(1) + w200OffsetNC(1), ...
              w200ColBnd(1) + matchCenter(2) + w200OffsetNC(2)] ;
    % - Build curve around indicator center, match needle origin and
    %  rotation direction.
    curveRowIds = round( needleCenter(1) - curveRadius * cos( 0:0.02:2*pi )) ;
    curveColIds = round( needleCenter(2) + curveRadius * sin( 0:0.02:2*pi )) ;
    % - Extract "signal" or sample along curve, perform 1D convolution.
    %  Manage circularity by tripling sample and working on middle part
    %  (crappy, must be overworked).
    curveSample = I_flat( sub2ind( size(I_flat), curveRowIds, curveColIds )) ;    
    sampleConv  = conv( repmat( curveSample, 1, 3 ), ...
        ones( 1, kernelSize )/kernelSize, 'same' ) ;
    nSamples    = numel( curveSample ) ;
    sampleConv  = sampleConv(nSamples + (1:nSamples)) ;
    needleAngles(fId) = -originAngle + ...
        360/nSamples * find( sampleConv == max(sampleConv), 1 ) ;
    fprintf( '%-20s: processing time = %.2fs.\n', D_jpg(fId).name, toc ) ;
    if display 
        figure() ;
        set( gcf, 'Units', 'normalized', 'Position', [0.1,0.1,0.8,0.8] ) ;
        % - Plot image, window "200", curve, center, needle.
        subplot( 2, 2, 1 ) ;  hold on ;
        imshow( I_flat/max(I_flat(:)) ) ;
        plot( needleCenter(2), needleCenter(1), 'xb', curveColIds, curveRowIds, 'r' ) ;
        plot( [reshape( [w200ColBnd; w200ColBnd], 1, [] ), w200ColBnd(1)], ...
            [w200RowBnd, fliplr(w200RowBnd), w200RowBnd(1)], 'g' ) ;
        needleTip = [needleCenter(1) - cosd( needleAngles(fId)+originAngle ) * needleLength, ...
            needleCenter(2) + sind( needleAngles(fId)+originAngle ) * needleLength] ;
        plot( [needleCenter(2), needleTip(2)], [needleCenter(1), needleTip(1)], ...
            'b', 'LineWidth', 3 ) ;
        % - Plot window "200" content and match center.
        subplot( 2, 2, 2 ) ;  hold on ;
        imshow( w200 ) ;
        plot( matchCenter(2), matchCenter(1), 'rx', 'LineWidth', 3, 'MarkerSize', 10 ) ;        
        % - Plot "signal" along curve, convolution, angle.
        subplot( 2, 2, 3 ) ;  hold on ;  grid on ;
        title( D_jpg(fId).name ) ;
        angleSample = 0:360/(nSamples-1):360 ;
        plot( angleSample, curveSample, 'b', angleSample, sampleConv, 'r' ) ;
        line( [needleAngles(fId) needleAngles(fId)], ylim, 'Color', [0, 1, 0] ) ;
        % - Text: angle, ..
        subplot( 2, 2, 4 ) ;  hold on ;
        set(gca, 'Visible', 'off' ) ;
        text( 0.1, 0.5 , sprintf( 'Angle = %.1f°', needleAngles(fId)), 'FontSize', 20 ) ;
    end
 end