Create a computer vision system using decision tree algorithms to solve a real-world problem : Corner detection – Harris

What is the primary characteristic of an edge in an image?

• A change in intensity in one direction

• A change in color

• A change in texture

• A change in shape

How are corners different from edges in terms of intensity change?

• Corners have intensity change in one direction

• Corners have intensity change in multiple directions

• Corners have intensity change only in the X direction

• Corners have no intensity change

What is the main purpose of the Harris corner detection method?

• To reduce image noise

• To enhance image brightness

• To detect corners by finding intensity changes in multiple directions

• To detect edges in an image

Which parameter in the Harris corner detection method is used to adjust the sensitivity of corner detection?

• Block size

• K size

• K parameter

• Sobel derivative

What is a limitation of corner detection when an image is scaled?

• Multiple corners may appear from a single corner

• Corners change color

• Corners disappear completely

• Corners become more distinct

Why is it beneficial to combine different feature detection methods?

• To simplify the algorithm

• To reduce memory usage

• To increase processing speed

• To improve object detection accuracy

Which of the following is NOT a method used in combination for feature detection?

• Harris corner detection

• Canny edge detection

• Gaussian blur

• Histogram of oriented gradients