Cutting off a segment of an Image that is blurry

Hello--

Basically I wanted to perform image analysis on a a hair switch and I was able to seperate the image from the background as follows:

If you look at the last image, all I want to do is basically cut off the top and bottom parts of the image because they are blurry. This can be a standard way of doing it that does the same crop for every picture I process because they will always be taken the same way.

The original pictures are here:

and

My code to get souly the hair is as follow (thank you image analyst for providing me with most of this):

[Brian Peoples]

% Demo to mask of hair switch.
% By Image Analyst.
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clearvars;
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
fprintf('Beginning to run %s.m ...\n', mfilename);

%-----------------------------------------------------------------------------------------------------------------------------------
% Read in image.
file = 'C:\Users\bpeoples\Downloads\MATLAB GLOSS MEASUREMENTS\Sample_Image_Folder\Measurements\Blonde_Hair_Diffused\3CROP_trial 3';
filename = dir(fullfile(file, '*.jpg'));
total_images = numel(filename);
f = fullfile(file, filename(1).name);
rgbImage = imread(f);
[rows, columns, numberOfColorChannels] = size(rgbImage);
% Display the RGB image full size.
subplot(2, 2, 1);
imshow(rgbImage, []);
axis('on', 'image');
caption = sprintf('Original Image : "%s"', filename(1).name);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.

% Set up figure properties:
% Enlarge figure to full screen.
hFig1 = gcf;
hFig1.Units = 'Normalized';
hFig1.WindowState = 'maximized';
% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
hFig1.Name = 'Demo by Image Analyst';

% Do color segmentation to get the blue tape.
[BW,maskedRGBImage] = createMask(rgbImage);
mask = ~BW;
% Get rid of blobs smaller than 10,000 pixels.
mask = bwareaopen(mask, 10000);

% Display the binary image.
subplot(2, 2, 2);
imshow(mask, []);
axis('on', 'image');
caption = sprintf(' Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.

% Get the area and centroid.
labeledImage = bwlabel(mask);
props = regionprops(labeledImage, 'Area', 'Centroid');
allAreas = [props.Area]
xy = vertcat(props.Centroid);
% Find out which one is closest to the middle.
x = xy(:, 1);
middlex = columns/2
distanceFromMiddle = abs(x - middlex)
[minDistance, indexOfMiddle] = min(distanceFromMiddle)
% Keep the middle blob.
hairMask = ismember(labeledImage, indexOfMiddle);
hairMask = imfill(hairMask, 'holes');
%convert masked image to rgb
I4 = cat(3,hairMask,hairMask,hairMask);
I5 = uint8(I4).*rgbImage;
% Display the RGB image full size.
subplot(2, 2, 3);
imshow(hairMask, []);
axis('on', 'image');
caption = sprintf('Hair Mask');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Display the RGB image full size.
subplot(2, 2, 4);
imshow(I5, []);
axis('on', 'image');
caption = sprintf('RGB Hair Mask');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;


%=====================================================================================================
function [BW,maskedRGBImage] = createMask(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.
%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
%  auto-generated code from the colorThresholder app. The colorspace and
%  range for each channel of the colorspace were set within the app. The
%  segmentation mask is returned in BW, and a composite of the mask and
%  original RGB images is returned in maskedRGBImage.

% Auto-generated by colorThresholder app on 06-Jul-2020
%------------------------------------------------------

% Convert RGB image to chosen color space
I = rgb2hsv(RGB);

% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.580; %orig .410
channel1Max = 0.670; %orig. .670

% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.000;
channel2Max = 1.000;

% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.000;
channel3Max = 1.000;

% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
	(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
	(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;

% Initialize output masked image based on input image.
maskedRGBImage = RGB;

% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;

end

[Brian Peoples]

If you look at the subplot, right around 500 and 3500 is where it gets blurry, so if I could do a cut at those spots that'd be ideal and just have those parts removed from the image section.

Answer 1

[Image Analyst]

Can't you just erase above and below those lines?

rgbImage(1 : 500, :, :) = 0;
rgbImage(3500 : end, :, :) = 0;

[Brian Peoples]

YES ahaha! I literally did that a second after I posted the question and forgot about it. I really do apologize for wasting your time

[Brian Peoples]

I just posted a new question @ https://www.mathworks.com/matlabcentral/answers/562313-how-to-remove-black-from-background-of-cropped-image

not too important, but if you could help it would be ideal