Implementation of Snake Algorithmm for finding contours of Hand

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Explorer 2014-2-6

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/115139-implementation-of-snake-algorithmm-for-finding-contours-of-hand

评论： Nhat Nguyen Thanh Minh 2020-10-29

采纳的回答： Image Analyst

I am following a research paper in which contour of hand is determined as shown in Figure 4.

In this paper, snakes were used to perform segmentation. A snake can be defined as an energy-minimizing spline guided by external restraining forces and influenced by image forces, which tends to localize it in features such as lines and edges. It is therefore an active contour that evolves dynamically relevant to the contours of the image. The snake is represented as a parametric curve by r(s) = (x(s),y(s)), with s(0, 1). Its functional energy can be expressed as:

Where Eint represents the internal energy of the snake, Eimg image forces and Eres external restraining forces.

Can you help in coding for this?

This is the image whose contours I need to find.

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Walter Roberson 2014-2-7

Asking how to proceed is an algorithms or theory question, not a MATLAB question.

Amelia Kartika 2018-2-24

How this coding for procced

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Image Analyst 2014-2-6

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https://ww2.mathworks.cn/matlabcentral/answers/115139-implementation-of-snake-algorithmm-for-finding-contours-of-hand#answer_123523

activecontour_demo.m

See my activecontour demo, attached. It will find the hand.

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Explorer 2014-2-9

编辑：Explorer 2014-2-9

sd_ycbcr.m

I have done some modifications in code in order to get contour of desired image.

Problem:

1. Not getting perfect contour

2. I need hand contour image as binary image like this

________________________________________________________________________

clc; % Clear the command window.

close all; % Close all figures (except those of imtool.)

imtool close all; % Close all imtool figures if you have the Image Processing Toolbox.

clear; % Erase all existing variables. Or clearvars if you want.

workspace; % Make sure the workspace panel is showing.

format long g;

format compact;

fontSize = 15;

image=imread('C:\Users\Explorer\Documents\MATLAB\ASL_signs\A.jpg');

rimage=imresize(image, 0.20);

grayImage = rgb2gray(rimage);

% Get the dimensions of the image.

% numberOfColorBands should be = 1.

[rows, columns, numberOfColorBands] = size(grayImage);

if numberOfColorBands > 1

% It's not really gray scale like we expected - it's color.

% Convert it to gray scale by taking only the green channel.

grayImage = grayImage(:, :, 2); % Take green channel.

end

% Display the original gray scale image.

subplot(2, 2, 1);

imshow(grayImage, []);

axis on;

title('Original Grayscale Image', 'FontSize', fontSize);

% Enlarge figure to full screen.

set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);

% Give a name to the title bar.

set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')

drawnow;

% Let's compute and display the histogram.

[pixelCount, grayLevels] = imhist(grayImage);

subplot(2, 2, 2);

bar(grayLevels, pixelCount);

grid on;

title('Histogram of original image', 'FontSize', fontSize);

xlim([0 grayLevels(end)]); % Scale x axis manually.

% % Construct an initial mask that is the convex hull of everything.

% subplot(2, 2, 2);

% % mask = grayImage < 175; % Use for eight.tif

% mask = grayImage > 150; % Use for coins.png

% mask = bwconvhull(mask, 'Union');

%imshow(mask);

% axis on;

% title('Initial mask', 'FontSize', fontSize);

% drawnow;

% Construct an initial mask that is the convex hull of everything.

subplot(2, 2, 2);

mask = sd_ycbcr(rimage) ; % skin detection function

imshow(mask);

axis on;

title('Initial mask', 'FontSize', fontSize);

drawnow;

% Now find the improved outer boundary using active contours.

bw = activecontour(grayImage, mask, 400, 'edge');

subplot(2, 2, 3);

imshow(bw);

axis on;

title('Outer Boundary Mask', 'FontSize', fontSize);

drawnow;

% Display the original gray scale image in the lower left

% So we can display boundaries over it.

subplot(2, 2, 4);

imshow(grayImage, []);

axis on;

hold on;

% Display the initial contour on the original image in blue.

% Display the final contour on the original image in red.

contour(mask,[0 0],'b', 'LineWidth', 4);

contour(bw,[0 0],'r', 'LineWidth', 4);

title('Image with initial and final contours overlaid', 'FontSize', fontSize);

________________________________________________________________________

Output:

Amy Phan 2017-4-2

I tried this code but I'm not receiving any outline for my image. This is the outcome:

The image I'm using is an MRI image and I'm trying to use the snake method to outline the heart but I'm having issues with the thresholding. Any suggestions?