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SKEM4133 MVS 2324-1 Topic 5

Total questions: 10

Worksheet time: 10mins

Name
Class
Date
1.

Object _________ are the most important cues that link an intensity image with its interpretation.

a)

shapes

b)

boundaries

c)

colors

d)

textures

2.

An edge detection technique based on the zero-crossings of the _________ explores the fact that a step edge corresponds to __________in the image function.

a)

second derivative, an edge blurring

b)

first derivative, an abrupt change

c)

second derivative, an abrupt change

d)

first derivative, an edge detection

3.

The ________ of the image function should have an extremum at the position corresponding to the edge in the image, and so the _________ should be zero at the same point.

a)

second derivative, first derivative

b)

first derivative, second derivative

c)

second derivative, third derivative

d)

third derivative, second derivative

4.

After image convolution with ___________, the locations in the convolved image where the zero level is crossed correspond to the positions of edges.

a)

derivative of the Gaussian filter

b)

derivative of the Laplacian filter

c)

derivative of the Gaussian operator

d)

derivative of the Laplacian filter

5.

The following statements are TRUE about the Canny edge detector EXCEPT:

a)

Canny edge detection operator uses a multi-stage algorithm

b)

It was developed by John F. Canny

c)

It detects a wide range of edges in images

d)

It can be used to smooth out sharp edges in images

6.

____________ is an important part of image processing as it facilitates the computational identification and _________ of images into distinct parts.

a)

Edge detection, separation

b)

Edge smoothing, separation

c)

Edge detection, grouping

d)

Edge blurring, grouping

7.

Choose the correct sequence for the Canny edge detection process:

a)

Gaussian filtering, Image gradient, Non-maximum suppression, Hysteresis

b)

Image gradient, Gaussian filtering, Non-maximum suppression, Hysteresis

c)

Gaussian filtering, Hysteresis, Non-maximum suppression, Image gradient

d)

Gaussian filtering, Non-maximum suppression, Image gradient, Hysteresis

8.

As noise can mislead the result in finding edges, we have to _____ the noise. Therefore, the image is smoothed by applying a _______________.

a)

reduce, Laplacian filter

b)

reduce, Gaussian filter

c)

eliminate, Gaussian filter

d)

eliminate, Laplacian filter

9.

Non-maximum suppression is necessary to convert the _______ in the image of the gradient magnitudes to _________.

a)

blurred edges, sharp edges

b)

sharp edges, blurred edges

c)

missing edges, clear edges

d)

missing objects, sharp edges

10.

In image processing, ________compares two images to build an intermediate image. The function takes two binary images that have been ________ at different levels.

a)

hysteresis, thresholded

b)

convolution, smoothed

c)

threshold, smoothed

d)

convolution, thresholded