Help with Image Processing code
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hello i have the following code that i saw in an example i tried to understand it and apply it to my code but i don't find a solution to my issue if someone can help thanks i want to have the washer at the end
%% image processing detection
clc; % Clear command window.
clear; % Delete all variables.
close all; % Close all figure windows except those created by imtool.
imtool close all; % Close all figure windows created by imtool.
workspace; % Make sure the workspace panel is showing.
%% read an image
I = im2double(imread('washer.png'));
subplot(3,3,1)
imshow(I);
title('Original Image');
%% Step 2: Detect Entire washer
[~,threshold] = edge(I,'sobel');
fudgeFactor = 0.7;
BWs = edge(I,'sobel',threshold * fudgeFactor);
% Display the resulting binary gradient mask.
subplot(3,3,2)
imshow(BWs);
title('Binary Gradient Mask');
%% Step 3: Dilate the Image
se90 = strel('line',3,90);
se0 = strel('line',3,0);
% Display the resulting dilated gradient mask.
BWsdil = imdilate(BWs,[se90 se0]);
subplot(3,3,3)
imshow(BWsdil)
title('Dilated Gradient Mask')
%% Step 4: Fill Interior Gaps
BWdfill = imfill(BWsdil,'holes');
subplot(3,3,4)
imshow(BWdfill)
title('Binary Image with Filled Holes')
%% Step 5: Remove Connected Objects on Border
BWnobord = imclearborder(BWdfill,4);
subplot(3,3,5)
imshow(BWnobord)
title('Cleared Border Image')
%% Step 6: Smooth the Object
seD = strel('disk',1);
BWfinal = imerode(BWnobord,seD);
BWfinal = imerode(BWfinal,seD);
subplot(3,3,6)
imshow(BWfinal)
title('Segmented Image');
%% Step 7: Visualize the Segmentation
subplot(3,3,7)
imshow(labeloverlay(I,BWfinal))
title('Mask Over Original Image')
8 comentarios
Image Analyst
el 21 de Abr. de 2020
You forgot to attach 'washer.png', and you forgot to say why that code is not a solution for you. Please read this link.
BERG
el 21 de Abr. de 2020
Image Analyst
el 21 de Abr. de 2020
It looks like that is the roadway under a wheeled vehicle. What is your definition of what kind of objects you want to find? Bright things?
BERG
el 21 de Abr. de 2020
Image Analyst
el 21 de Abr. de 2020
So you want things that are unusual in an otherwise-uniform-ish image? Try running stdfilt() on it. That will highlight things that very a lot within the window.
BERG
el 21 de Abr. de 2020
Mrutyunjaya Hiremath
el 26 de Abr. de 2020
Hello BERG,
Are you expecting something like this?

BERG
el 28 de Abr. de 2020
Respuesta aceptada
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