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The choice of an image coordinate system is a matter of convention in most cases. As introduced in the lectures, we will use the left handed image coordinate system, with the first axis (*u*) pointing right and the second axis (*v*) pointing down. Coordinates of a point are then written as an algebraic **column** vector (euclidean) . In Matlab, we will write e.g.

[u;v]

Since *1-based* indexing is used in Matlab, the **centre** of the top left pixel has coordinates `[1;1]`

and the centre of the bottom right pixel has coordinates `[count_u; count_v ]`

, where `count_u`

is number of image columns and `count_v`

is number of image rows (both in pixels). See figure 1.

When drawing points or lines in Matlab, correct orientation of ordinate must be set.

plot( u, v ); set( gca, 'ydir', 'reverse' );

It is also possible to draw a bitmap image first, and then draw points or lines over the bitmap. Correct orientation is then set automatically by imaging the bitmap.

im = imread( 'image.jpg' ); image( im ); hold on plot( u, v ); hold off

Matlab considers images as ordinary matrices, so the standard matrix indexation (row, column) is used. Let `[u;v]`

be the integer coordinates in the grayscale image (centre of a pixel). Then the intensity of the pixel is obtained as

im(v,u)

- Do not trust any results unless you verified them.
- Always verify your results.
- Try to visualize your results
- Each Matlab command has help. E.g. for
`plot`

help plot % text version doc plot % html version

- Try to encapsulate general tasks into a functions and reuse them.
- Remind the rule 1.

Matlab has a powerful debugger. Either put breakpoints everywhere you want, or use the command `keyboard`

in your code to stop processing at the place. Exit the debugging mode:

dbquit

You can also start debugging automatically in case of error by turning on

dbstop error

Vectors are stored as column matrices.

u = [1;2]; X = [1;2;3]; Xmore = [1 2 3; 4 5 6]'; % transpose at the end

Vectors are multiplied by a matrices on the left:

P = [1 0 0 -5; 0 1 0 -6; 0 0 1 1]; % a camera ux_homog = P * [X;1]; % projection

I = eye(3); % 3x3 identity I2 = diag( [1 1 1] ); % same result Z = zeros(3); % 3x3 matrix of zeroes O = ones(3); % 3x3 matrix of ones

X1 = [1;2;3]; X2 = [4;5;6]; d2 = norm(X1-X2); % cannot be used for more vectors d2 = sqrt(sum((X1-X2).^2)); % for matrices with points stored in columns

u1 = [4;5;1]; u2 = [7;8;1]; dot12 = u1' * u2;

u1 = [4;5;1]; u2 = [7;8;1]; u12x = cross(u1,u2); % verification of orthogonality by dot product % (remember the recommendations 1 and 2) u12x' * u1 % should be zero u12x' * u2 % should be zero

courses/tdv/labs/matlab_and_geometry.txt · Last modified: 2019/09/13 11:38 (external edit)