Image SegmentationActive Contours

By:- Abhishek Tiwari

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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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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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Contour Evolution Example

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Contour Evolution Example

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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');

Results

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Thank YouFor my complete course on Image processing using MATLAB ,

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