tracking a moving boundary in matlab

To track a moving boundary in MATLAB, the general approach is to use image processing techniques to detect the boundary in successive frames and then use computer vision algorithms to track the movement of the detected boundary. One common technique for detecting the boundary of an object in an image is edge detection.

Here's some sample code for tracking a moving boundary using edge detection:

main.m
% Load the first image
img = imread('first_frame.jpg');

% Detect the boundary using edge detection
edge_img = edge(img, 'canny');

% Initialize the boundary location
boundary = bwperim(edge_img);

% Display the original image with boundary superimposed
imshow(img)
hold on
visboundaries(boundary, 'Color', 'r');

% Loop through subsequent frames
for i = 2: num_frames
    % Load the next image
    img = imread('frame' + i + '.jpg');
    
    % Detect the boundary using edge detection
    edge_img = edge(img, 'canny');
    
    % Track the boundary movement using optical flow
    flow = opticalFlowLK('NoiseThreshold',0.009);
    flow = estimateFlow(flow, edge_img);
    pts = [x,y];
    [pts, validIdx] = step(opticalFlowLK, edge_img);
    boundary = pts(validIdx, :);
    
    % Display the current image with boundary superimposed
    imshow(img)
    hold on
    visboundaries(boundary, 'Color', 'r');
end
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This code uses the edge function to detect the edges in the image, then uses bwperim to convert the edge map to a binary image representing the boundary. Optical flow is used to track the movement of the boundary between frames. The visboundaries function is used to display the boundary on top of the original images.

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