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https://github.com/hritik5102/blob-detection-using-matlab
Blob detection and analysis using Matlab
https://github.com/hritik5102/blob-detection-using-matlab
blob-analysis blob-detection color-detection color-tracker image-processing matlab matlab-codes matlab-image-processing-toolbox matlab-interface matlab-script
Last synced: 22 days ago
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Blob detection and analysis using Matlab
- Host: GitHub
- URL: https://github.com/hritik5102/blob-detection-using-matlab
- Owner: hritik5102
- Created: 2019-09-28T18:47:56.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-10-22T20:46:30.000Z (about 4 years ago)
- Last Synced: 2024-10-25T07:32:58.574Z (2 months ago)
- Topics: blob-analysis, blob-detection, color-detection, color-tracker, image-processing, matlab, matlab-codes, matlab-image-processing-toolbox, matlab-interface, matlab-script
- Language: MATLAB
- Homepage:
- Size: 71.4 MB
- Stars: 3
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
## 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
```matlab
load sampleFrames.mat
subplot(1,3,1)
imshow(vidFrame1)
```
> ### Threshold image
```matlab
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
```matlab
noise = strel('disk' , 3);
open = imopen(BW, noise);
subplot(1,3,3);
imshow(open);
```
> ### Blob Analysis
```matlab
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
```matlab
% 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
```matlab
release(blob)
```
### Result
