How to scaling/ registering an image in relation to another, to have the two images in the same coordinate system?

I already make a question in other post about this,but I have no answers

These are the images

I have two images (manual segmentation red line) and automated segmentation (blue line). What I want to is scaling the first image and crop in order to the points in the first are in the same coordinate system and correspond to the points in the second (manual segmentation). And then crop the image (automated segmentation) for this have the same dimensions as the first, in the same scale .

While I was trying the solution that was more similar of mine this is in these link http://www.mathworks.com/help/images/examples/registering-an-image-using-normalized-cross-correlation.html. So I try to do it, the code is below, but it appears these error, what am I doing wrong for the xbegin and offset was negative?

% Algorithm for image validation

% Open the two images which will be compared

name2=input('Image name ( automated segmentation)     ','s');
img_automated=imread(name2,'png');
figure (1), imshow(img_automated), title('Image automated')

name=input('Image name ( manual segmentation)     ','s');
img_manual=imread(name,'png');
img_manual_gray=rgb2gray(img_manual);

figure (2), imshow (img_manual),title('Image manual')

img_automated_gray=rgb2gray(img_automated);
%img_double=im2double(img_automated_gray);
figure (3), imshow (img_automated_gray), title (' Image converted to double ');
imcontrast
%uiwait(img_automated_gray)

img_automated_eq=adapthisteq(img_automated_gray);
figure (5), imshow (img_automated_eq), title (' Image after histogram equalization ');
img_automated_gray=rgb2gray(img_automated);

figure (6), imshowpair(img_manual,img_automated_eq)
title('Images overlap')

%Step 2: Choose Subregions of Each Image

%It is important to choose regions that are similar.The image sub_automated
%will be the template, and must be smaller than the image sub_manual. 

% interactively
[sub_manual,rect_manual] = imcrop(img_manual); % choose the pepper below the onion
[sub_automated,rect_automated] = imcrop(img_automated_gray); % choose the whole onion

% display sub images
figure(8), imshow(sub_automated)
figure(9), imshow(sub_automated)

%Step 3: Do Normalized Cross-Correlation and Find Coordinates of Peak
%Calculate the normalized cross-correlation and display it as a surface plot.
% The peak of the cross-correlation matrix occurs where the sub_images are
% best correlated. normxcorr2 only works on grayscale images, so we pass it
% the red plane of each sub image.

c = normxcorr2(sub_automated(:,:,1),sub_manual(:,:,1));
figure (10), surf(c), shading flat

%Step 4: Find the Total Offset Between the Images

%The total offset or translation between images depends on the location
%of the peak in the cross-correlation matrix, and on the size and position 
%of the sub images.

% offset found by correlation
[max_c, imax] = max(abs(c(:)));
[ypeak, xpeak] = ind2sub(size(c),imax(1));
corr_offset = [(xpeak-size(sub_automated,2))
               (ypeak-size(sub_automated,1))];

% relative offset of position of subimages
rect_offset = [(rect_manual(1)-rect_automated(1))
               (rect_manual(2)-rect_automated(2))];

% total offset
offset = corr_offset + rect_offset;
xoffset = offset(1);
yoffset = offset(2);

%Step 5: See if the Onion Image was Extracted from the Peppers Image

%Figure out where onion falls inside of peppers.
xbegin = round(xoffset+1);
xend   = round(xoffset+ size(img_automated_gray,2));
ybegin = round(yoffset+1);
yend   = round(yoffset+size(img_automated_gray,1));

% extract region from peppers and compare to onion
extracted_automated =img_manual(ybegin:yend,xbegin:xend,:);
if isequal(img_automated_gray,extracted_automated)
   disp('extracted_automated.png was extracted from img_automated.png')
end

%Step 6: Pad the Onion Image to the Size of the Peppers Image
%Pad the automated image to overlay on manual, using the offset determined above.

recovered_automated = uint8(zeros(size(img_manual)));
recovered_onion(ybegin:yend,xbegin:xend,:) = img_automated_gray;
figure(11), imshow(recovered_automated)

figure (12), imshowpair(img_manual(:,:,1),recovered_automated,'blend')

[Image Analyst]

Is this an updated version of http://www.mathworks.com/matlabcentral/answers/170214-how-to-crop-and-scale-an-image-in-relation-to-another? You can edit existing posts you know.