To detect the dimensions of an object under an angle in a picture in MATLAB, you can use computer vision techniques like image segmentation, edge detection, and Hough transform.

Here are the general steps you can follow:

1. Load the image in MATLAB using the imread function.
2. Convert the image to grayscale using the rgb2gray function.
3. Apply edge detection using the edge function to obtain the edges of the object in the image.
4. Use the Hough transform function, hough, to detect lines in the image.
5. Find the peaks in the Hough transform accumulator array using the houghpeaks function.
6. Use the houghlines function to obtain the line segments corresponding to the detected peaks.
7. Filter the line segments to keep only the ones that correspond to the edges of the object.
8. Calculate the distance between the two edges to obtain the dimensions of the object.

Here's an example code snippet that demonstrates how to detect the dimensions of an object under an angle in MATLAB: 

% Load the image
img = imread('object.png');

% Convert to grayscale
gray_img = rgb2gray(img);

% Apply edge detection
edge_img = edge(gray_img, 'Canny');

% Perform Hough transform
[H,theta,rho] = hough(edge_img);
peaks = houghpeaks(H, 10);
lines = houghlines(edge_img,theta,rho,peaks);

% Filter lines to keep only the ones corresponding to the object edges
filtered_lines = [];
for k = 1:length(lines)
    if (abs(lines(k).theta) > 45) && (abs(lines(k).theta) < 135)
        filtered_lines = [filtered_lines; lines(k)];
    end
end

% Calculate distance between the two edges
distance = norm(filtered_lines(1).point1 - filtered_lines(2).point1);

% Display the image with the detected lines
imshow(img);
hold on;
for k = 1:length(filtered_lines)
    xy = [filtered_lines(k).point1; filtered_lines(k).point2];
    plot(xy(:,1), xy(:,2), 'LineWidth', 2, 'Color', 'green');
end

Note: This is just an example and may need to be adjusted for your specific use case.