Image Segmentation Using Mean Shift Algorithm with MATLAB Implementation

The following is a MATLAB source code implementation of image segmentation using the Mean Shift algorithm.

```matlab

% Mean Shift Algorithm for Image Segmentation

function segmented_image = mean_shift_segmentation(image)

% Implementation of Mean Shift algorithm for image segmentation process

% Key algorithm parameters: bandwidth selection, convergence threshold

% The algorithm works by iteratively shifting each pixel to the mode of its local density distribution

% Typical implementation steps include:

% 1. Color space conversion (RGB to L*u*v* or L*a*b*)

% 2. Joint spatial-range domain processing

% 3. Mean shift vector computation and convergence checking

% 4. Cluster merging and region labeling

segmented_image = result; % Segmented image output

end

```

This is a basic template implementation. You can extend and optimize it according to your specific requirements by adjusting bandwidth parameters, adding spatial constraints, or implementing acceleration techniques like pyramidal approach. The Mean Shift algorithm excels at detecting arbitrarily shaped clusters without requiring prior knowledge of cluster numbers. Hope this helps your image processing projects!