Learn about Active contour segmentation in MATLAB. A simple and lucid way to understand image segmentation using examples with MATLAB code.

1. Image Segmentation
Active Contours
By:- Abhishek Tiwari
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2. Introduction
 Active contours, also known as snakes, is a framework for getting object
outline contour
 The framework minimizes an energy associated to the current contour as a
sum of internal and external energies
 External energy expression is derived such that it is minimum at object boundary
 Internal energy regulates the shape of contour, controlling its curvature, shape
regularity, etc.
 More energy terms can be introduced as per user application such as initializing
multiple snakes and defining attraction energy between them, etc.
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3. Advantages & Limitations
 Advantages of snakes
 Autonomous and self-adapting in their search for minimal energy
 Can track moving objects in temporal as well as spatial direction
 Custom energies can be defined to enhance contour evolution
 Limitations of snakes
 Can get stuck in local minima states
 Can miss minute features in the process of minimizing whole contour energy
 May require higher computation time
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4. Contour Evolution Example
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5. Contour Evolution Example
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6. Our Implementation
clear all; close all; clc;
% Read an input image
A = imread('coins1.jpg');
% Convert the image to grayscale
A = rgb2gray(A);
% Generate mask for active contour initialization
mask = zeros(size(A));
mask(10:end-10,10:end-10) = 1;
% Segment the image using active contour method
bw = activecontour(A, mask, 300);
% Display original and segmented images
figure, subplot(1, 2, 1), imshow(A), title('Original image');
subplot(1, 2, 2), imshow(bw), title('Segmented image');

7. Results
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8. Thank You
For my complete course on Image processing using MATLAB ,
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