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blob-detection-using-matlab's Introduction

Blob detection and analysis using Matlab

A Blob is a group of connected pixels in an image that share some common property ( E.g grayscale value ).

Steps includes for blob analysis on image

Load sample frames

   
   load sampleFrames.mat
   subplot(1,3,1)
   imshow(vidFrame1)

Threshold image

I = rgb2hsv(vidFrame1);

% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.333;
channel1Max = 0.561;

% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.327;
channel2Max = 1.000;

% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.186;
channel3Max = 1.000;

% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
    (I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
    (I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;

subplot(1,3,2)
imshow(BW)

Remove disturbances

   
   noise = strel('disk' , 3);

   open = imopen(BW, noise);
   subplot(1,3,3);
   imshow(open);

Blob Analysis

blob = vision.BlobAnalysis('MinimumBlobArea',200,...    
 'MaximumBlobArea',5000);
 % to perform a blob analysis on the video frame we need to use step
 % function :- parameter => (blob analysis system object , input image i.e open)
 % function output 3 :- area , centroid , bounding box

 [objectArea , objCentroid , bboxout] = step(blob , open);

Annotate image

  
  % now we get a bounding box cordinates of detected ball let apply contour
  % over the detected ball using rectangle 

  rectangle = insertShape(vidFrame1 , 'rectangle',bboxout , 'Linewidth' , 4 , 'Color',...
      [155 164 155]);

  figure 
  subplot(1,2,1)
  imshow(rectangle)

Clean up

   release(blob)

Result

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