Edge detection (Canny) in Computer Vision - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal of the Canny edge detection algorithm?

The main goal of the Canny edge detection algorithm is to find the edges in an image accurately by detecting sharp changes in brightness while reducing noise and avoiding false edges.

intermediate

List the main steps of the Canny edge detection process.

1. Noise reduction using a Gaussian filter.<br>2. Finding the intensity gradient of the image.<br>3. Non-maximum suppression to thin edges.<br>4. Double threshold to identify strong and weak edges.<br>5. Edge tracking by hysteresis to finalize edges.

intermediate

Why does Canny edge detection use two thresholds instead of one?

Canny uses two thresholds to separate strong edges from weak edges. Strong edges are definitely edges, while weak edges are only considered edges if they connect to strong edges. This helps reduce noise and false detections.

beginner

What role does the Gaussian filter play in Canny edge detection?

The Gaussian filter smooths the image to reduce noise before detecting edges. This helps prevent false edges caused by small fluctuations in pixel values.

intermediate

Explain what non-maximum suppression does in the Canny algorithm.

Non-maximum suppression thins the edges by keeping only the pixels that are local maxima in the gradient direction. This means it removes pixels that are not the strongest edge points, making edges thinner and clearer.

What is the first step in the Canny edge detection algorithm?

A Perform edge tracking by hysteresis

B Find intensity gradient

C Apply double threshold

D Apply Gaussian filter to reduce noise

The first step is to smooth the image with a Gaussian filter to reduce noise before detecting edges.

Why does Canny edge detection use two thresholds?

A To detect colors

B To separate strong edges from weak edges

C To blur the image

D To speed up the algorithm

Two thresholds help distinguish strong edges from weak edges, improving edge detection accuracy.

What does non-maximum suppression do?

A Thins edges by keeping only local maxima

B Blurs the image

C Detects corners

D Removes all edges

Non-maximum suppression thins edges by keeping only the strongest pixels along the gradient direction.

Which filter is used in Canny to reduce noise?

A Gaussian filter

B Median filter

C Sobel filter

D Laplacian filter

The Gaussian filter smooths the image to reduce noise before edge detection.

What is the final step in the Canny edge detection process?

A Non-maximum suppression

B Double threshold

C Edge tracking by hysteresis

D Gradient calculation

Edge tracking by hysteresis finalizes edges by connecting weak edges to strong edges.

Describe the full process of the Canny edge detection algorithm in your own words.

Think about how the algorithm finds edges step by step, starting from smoothing the image.

Explain why using two thresholds improves edge detection compared to using just one.

Consider how weak edges might be noise or real edges depending on their connection.