Sir, How to extract color and shape features for a leaf image?

To detect disease in an image we need color and shape features to relate to the database.

Answer 1

[Shree Harsha Kodi]

% Step 1: Read the leaf image
leafImage = imread('leaf.jpg');

% Step 2: Preprocess the image (if needed)

% Step 3: Extract color features
hsvImage = rgb2hsv(leafImage);
hueChannel = hsvImage(:, :, 1);
hueMean = mean(hueChannel(:));

% Step 4: Extract shape features
binaryImage = imbinarize(rgb2gray(leafImage), graythresh(leafImage));
binaryImage = imopen(binaryImage, strel('disk', 5));
leafArea = regionprops(binaryImage, 'Area');

% Step 5: Combine the extracted features
featureVector = [hueMean, leafArea.Area];

% Step 6: Perform further analysis or comparison with a database

% Display the extracted features
disp('Extracted Features:');
disp('-------------------');
disp(['Hue Mean: ', num2str(hueMean)]);
disp(['Leaf Area: ', num2str(leafArea.Area)]);
disp('-------------------');

Answer 2

[Image Analyst]

Search for the tag leaf. There have been so many in the past and I've given code for lots of them.

https://www.mathworks.com/matlabcentral/answers/?term=tag%3A%22leaf%22

For example, the attached.

% Mask a leaf out of an RGB image.
clc;    % Clear the command window.
clear all;
close all;
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 24;
%===============================================================================
% Read in leaf color demo image.
folder = pwd
baseFileName = 'leaf.jpg';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
    % Didn't find it there.  Check the search path for it.
    fullFileName = baseFileName; % No path this time.
    if ~exist(fullFileName, 'file')
        % Still didn't find it.  Alert user.
        errorMessage = sprintf('Error: %s does not exist.', fullFileName);
        uiwait(warndlg(errorMessage));
        return;
    end
end
rgbImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows, columns, numberOfColorChannels] = size(rgbImage);
% Display the original color image.
subplot(2, 2, 1);
imshow(rgbImage);
title('Original Color Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'Outerposition', [0, 0, 1, 1]);
% Extract the individual red, green, and blue color channels.
% redChannel = rgbImage(:, :, 1);
% greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
% Create a mask of the background only.
mask = blueChannel > 200;
% Display the mask image.
subplot(2, 2, 2);
imshow(mask);
title('Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Mask out the leaf, leaving only the background.
% Mask the image using bsxfun() function
maskedRgbImage = bsxfun(@times, rgbImage, cast(mask, 'like', rgbImage));
% Display the mask image.
subplot(2, 2, 3);
imshow(maskedRgbImage);
title('Background-Only Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Mask out the background, leaving only the leaf.
% Mask the image using bsxfun() function
maskedRgbImage = bsxfun(@times, rgbImage, cast(~mask, 'like', rgbImage));
% Display the mask image.
subplot(2, 2, 4);
imshow(maskedRgbImage);
title('Leaf-Only Image', 'FontSize', fontSize, 'Interpreter', 'None');