How to remove scales and the black border from the segmented image

Question

Aashir Ahmed 2022-3-20

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1675969-how-to-remove-scales-and-the-black-border-from-the-segmented-image

回答： yanqi liu 2022-3-21

I need a matlab code to remove the scale and the black part from the segmented image. The segmentation was done using Otsus. Here is the code below for Otsus.

%% Otsu Thresholding
close all;
clear all;
clc
%%================================================================================================
location = 'demo.jpg';       %  folder in which your images exists
ds = imageDatastore(location)         %  Creates a datastore for all images in your folder
while hasdata(ds) 
    img = read(ds) ;             % read image from datastore
    figure, imshow(img);    % creates a new window for each image
%%=================================================================================================
n=imhist(img); % Compute the histogram
N=sum(n); % sum the values of all the histogram values
max=0; %initialize maximum to zero
%%================================================================================================
for i=1:256
    P(i)=n(i)/N; %Computing the probability of each intensity level
end
%%================================================================================================
for T=2:255      % step through all thresholds from 2 to 255
    w0=sum(P(1:T)); % Probability of class 1 (separated by threshold)
    w1=sum(P(T+1:256)); %probability of class2 (separated by threshold)
    u0=dot([0:T-1],P(1:T))/w0; % class mean u0
    u1=dot([T:255],P(T+1:256))/w1; % class mean u1
    sigma=w0*w1*((u1-u0)^2); % compute sigma i.e variance(between class)
    if sigma>max % compare sigma with maximum 
        max=sigma; % update the value of max i.e max=sigma
        threshold=T-1; % desired threshold corresponds to maximum variance of between class
    end
end
%%====================================================================================================
bw=im2bw(img,threshold/255); % Convert to Binary Image
figure ,imshow(bw); % Display the Binary Image
%%====================================================================================================
end