Additional QS
Mastering Edge Detection: Test Your Knowledge!
Put your image processing skills to the test with our comprehensive quiz on edge detection and thresholding techniques. This quiz covers a wide range of concepts, from basic definitions to advanced applications.
Key points of the quiz:
- 18 engaging multiple-choice questions
- Explore various edge detection techniques
- Understand the principles of thresholding
What is edge detection?
It is the operation of partitioning an image into component parts, or into separate objects.
It is the operation of isolating objects from the background by choosing a grey level π in the original image, and turning every pixel black or white according to whether its grey value is greater than or less than π.
It is the operation of detecting a local discontinuity in the pixel values which exceeds a given threshold.
It is the operation of adding the values of the three channels in an RGB image and dividing by three.
What is the result of thresholding when it is not possible to obtain a single threshold value which will isolate an object completely?
The object is isolated from its background.
The result of thresholding is particularly good.
Not all of the object are isolated from its background.
Different thresholds are used and the results are different.
What is the purpose of double thresholding?
To convert an RGB image into a greyscale image.
To isolate objects from the background by choosing two threshold values and applying thresholding to each pixel individually.
To cut the image into small pieces and apply thresholding to each piece individually.
To detect edges in an image.
What is the algorithm for non-maximum suppression for each pixel in the gradient image?
Compare the edge strength of the current pixel with the edge strength of the pixel in the positive and negative gradient directions. If the edge strength of the current pixel is the smallest compared to the other pixels with the same direction, the value will be preserved. Otherwise, the value will be suppressed.
Compare the edge strength of the current pixel with the edge strength of the pixel in the positive and negative gradient directions. If the edge strength of the current pixel is the largest compared to the other pixels with the same direction, the value will be preserved. Otherwise, the value will be suppressed.
Compare the edge strength of the current pixel with the edge strength of the pixel in the positive and negative gradient directions. If the edge strength of the current pixel is the average of the other pixels with the same direction, the value will be preserved. Otherwise, the value will be suppressed.
Compare the edge strength of the current pixel with the edge strength of the pixel in the positive and negative gradient directions. If the edge strength of the current pixel is equal to the sum of the other pixels with the same direction, the value will be preserved. Otherwise, the value will be suppressed.
What is the difference between a ramp edge and a step edge?
A ramp edge is where the grey values change suddenly, while a step edge is where the grey values change slowly.
A ramp edge is where the grey values change slowly, while a step edge is where the grey values change suddenly.
Both ramp and step edges are where the grey values change suddenly.
Both ramp and step edges are where the grey values change slowly.
What are the steps for the Canny Edge Detector?
Convolve image with Laplacian filter, perform non-maximum suppression, and apply hysteresis thresholding.
Convolve image with Sobel filter, perform non-maximum suppression, and apply hysteresis thresholding.
Convolve image with Gaussian filter, find magnitude and orientation of gradient, perform non-maximum suppression, and apply hysteresis thresholding.
Convolve image with Prewitt filter, perform non-maximum suppression, and apply hysteresis thresholding.
What is thresholding?
It is the operation of partitioning an image into component parts, or into separate objects.
It is the operation of converting an image into a greyscale image.
It is the operation of isolating objects from the background by choosing a grey level π in the original image, and turning every pixel black or white according to whether its grey value is greater than or less than π.
It is the operation of adding the values of the three channels in an RGB image and dividing by three.
What is the purpose of hysteresis thresholding in the Canny Edge Detector?
To amplify all gradient values
To suppress all gradient values except the local maxima
To enhance the noise in the image
To accept all weak edges that are βconnectedβ to strong edges
What is adaptive thresholding?
It is the operation of partitioning an image into component parts, or into separate objects.
It is the operation of isolating objects from the background by choosing a grey level π in the original image, and turning every pixel black or white according to whether its grey value is greater than or less than π.
It is the operation of cutting the image into small pieces, and applying thresholding to each piece individually when it is not possible to obtain a single threshold value which will isolate an object completely.
It is the operation of adding the values of the three channels in an RGB image and dividing by three.
What is the Sobel filter?
An edge thinning technique.
A filter used for edge detection in an image that detects two types of edges: horizontal and vertical edges.
A type of filter used in image processing.
A filter that provides differentiating and smoothing concurrently, detecting horizontal and vertical edges.
What is the difference between single thresholding and double thresholding?
Single thresholding is the operation of partitioning an image into component parts, while double thresholding is the operation of isolating objects from the background.
Single thresholding uses one threshold value to isolate objects from the background, while double thresholding uses two threshold values.
Single thresholding and double thresholding are the same thing.
Single thresholding is used for adaptive thresholding, while double thresholding is used for edge detection.
What is the difference between the Prewitt and Sobel filters?
The Prewitt filter detects two types of edges: horizontal and vertical edges, while the Sobel filter detects only vertical edges.
The Sobel filter detects two types of edges: horizontal and vertical edges, while the Prewitt filter detects only vertical edges.
The Prewitt filter detects two types of edges: horizontal and vertical edges, while the Sobel filter detects both horizontal and vertical edges.
The Sobel filter detects two types of edges: diagonal and vertical edges, while the Prewitt filter detects only diagonal edges.
Why are edges useful in image processing?
They allow to convert an RGB image into a greyscale image.
They help to isolate particular objects from their background.
They allow to detect the size of objects in an image.
All of the above.
Which of the following is NOT a situation where thresholding can be useful?
To remove unnecessary detail from an image, to concentrate on essentials.
To bring out hidden detail.
To add a varying background to text or a drawing.
To remove a varying background from text or a drawing.
What is the direction of the gradient of an image?
It is given by the magnitude of the gradient.
It is given by the rate of change in the x direction.
It is given by the angle between the x and y directions.
It is given by the ratio between the partial derivatives in the y and x directions.
By taking the mean of a number of images of the same scene, we can clean ................
Parallel bars
Scattered white pixels
Spikes
Circles
Best method to clean salt and pepper noise is ................
Low pass filtering
Outlier method
Rank order filtering
Median filtering
In spatial domain, periodic noise appears in the form of ...........
Parallel bars
Scattered white pixels
Spikes
Circles
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