How to improve the accuracy of Gaussian texture models?

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Hello,I want to use Gaussian texture models to detect traffic flow. How can I improve the accuracy of the model?
foregroundDetector = vision.ForegroundDetector('NumGaussians', 3, 'NumTrainingFrames', 50);
videoReader = VideoReader('VID_20211023_090102.mp4');
for i = 1:150
frame = readFrame(videoReader); % read the next video frame
foreground = step(foregroundDetector, frame);
end
figure; imshow(frame); title('Video Frame');
figure; imshow(foreground); title('Foreground');
se = strel('square', 3);
filteredForeground = imopen(foreground, se);
figure; imshow(filteredForeground); title('Clean Foreground');
blobAnalysis = vision.BlobAnalysis('BoundingBoxOutputPort', true, ...
'AreaOutputPort', false, 'CentroidOutputPort', false, 'MinimumBlobArea', 150);
bbox = step(blobAnalysis, filteredForeground);
result = insertShape(frame, 'Rectangle', bbox, 'Color', 'green');
numCars = size(bbox, 1);
result = insertText(result, [10 10], numCars, 'BoxOpacity', 1, 'FontSize', 14);
figure; imshow(result); title('Detected Cars');
videoPlayer = vision.VideoPlayer('Name', 'Detected Cars');
videoPlayer.Position(3:4) = [650,400]; % window size: [width, height]
se = strel('square', 3); % morphological filter for noise removal
ii=1;
while hasFrame(videoReader)
frame = readFrame(videoReader); % read the next video frame
% Detect the foreground in the current video frame
foreground = step(foregroundDetector, frame);
% Use morphological opening to remove noise in the foreground
filteredForeground = imopen(foreground, se);
% Detect the connected components with the specified minimum area, and
% compute their bounding boxes
bbox = step(blobAnalysis, filteredForeground);
% Draw bounding boxes around the detected cars
result = insertShape(frame, 'Rectangle', bbox, 'Color', 'green');
% Display the number of cars found in the video frame
numCars = size(bbox, 1);
numcar(ii)=numCars;
ii=ii+1;
result = insertText(result, [10 10], numCars, 'BoxOpacity', 1, ...
'FontSize', 14);
step(videoPlayer, result); % display the results
end

Accepted Answer

Himanshu
Himanshu on 9 Aug 2024
Hi,
I see that you are trying to improve the accuracy of your Gaussian texture model for detecting traffic flow.
To enhance the accuracy of your model, consider the following steps:
  • Increase the number of Gaussians in the mixture model to better capture the background variations.
  • Use more training frames to improve the model's understanding of the background.
  • Apply additional preprocessing steps to reduce noise and improve foreground detection.
  • Tune the parameters of the blob analysis to better detect objects of interest.
Please refer to the below documentations for more information.
  1. Foreground detection using Gaussian mixture models: https://www.mathworks.com/help/vision/ref/vision.foregrounddetector-system-object.html
  2. "VideoReader" class to learn about reading and processing video files in MATLAB: https://www.mathworks.com/help/matlab/ref/videoreader.html
  3. Morphological operations to understand how to apply noise reduction techniques: https://www.mathworks.com/help/images/morphological-dilation-and-erosion.html
  4. "vision.BlobAnalysis" system object to learn about detecting and analyzing connected components in binary images: https://www.mathworks.com/help/vision/ref/vision.blobanalysis-system-object.html
I hope this helps.

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