In Matlab, you can use the built-in functions "edge" and "corner" to detect edges and corners respectively. These functions allow you to specify a region of interest (ROI) by providing a binary mask that indicates the pixels within the ROI. Here's how you can do it:

1. Load your image into Matlab using the "imread" function.

img = imread('your_image.jpg');

2. Create a binary mask that indicates the pixels within the ROI. You can do this using any method that suits your application, for example, by manually drawing a region on the image using the "roipoly" function.

Create a binary mask that indicates the pixels within the ROI. You can do this using any method that suits your application, for example, by manually drawing a region on the image using the "roipoly" function.

roi_mask = roipoly(img); % Interactive ROI selection

3. Apply the "edge" function to the ROI by passing the binary mask as an optional argument.

edge_img = edge(img, 'Canny', [], [], [], roi_mask);

In the above example, the 'Canny' method is used for edge detection. The optional arguments are set to their default values.

4. Apply the "corner" function to the ROI by passing the binary mask as an optional argument.

corner_pts = corner(img, 'Harris', [], [], [], roi_mask);

In the above example, the 'Harris' method is used for corner detection. The optional arguments are set to their default values.

Note that the "edge" and "corner" functions also allow you to specify other parameters such as the method of edge or corner detection, the threshold values, etc. You can refer to the Matlab documentation for more information.