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Image Segmentation Quiz

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

What is the main goal of image segmentation?

a)

To enhance image brightness

b)

To divide an image into parts that correlate with real-world objects

c)

To compress image data

d)

To convert images to grayscale

2.

What is complete segmentation?

a)

Regions that overlap with each other

b)

A method of image compression

c)

A set of disjoint regions corresponding uniquely to objects

d)

An image with no segmentation

3.

Which of the following is a characteristic used in edge detection?

a)

File size

b)

Image resolution

c)

Brightness

d)

Color depth

4.

What is the simplest segmentation process mentioned?

a)

Edge-based segmentation

b)

Adaptive thresholding

c)

Region-based segmentation

d)

Gray level thresholding

5.

What does adaptive thresholding do?

a)

Uses a single global threshold for the entire image

b)

Changes the threshold dynamically based on local characteristics

c)

Ignores local variations in the image

d)

Only works with binary images

6.

What is the Chow and Kaneko approach used for?

a)

Detecting edges in images

b)

Enhancing image contrast

c)

Finding the optimal threshold for each sub-image

d)

Creating a binary image

7.

What is the purpose of the Otsu method?

a)

To apply adaptive thresholding

b)

To select an optimal threshold for image segmentation

c)

To reduce image noise

d)

To enhance image colors

8.

What is a drawback of the Otsu method?

a)

It requires manual threshold selection

b)

It is computationally expensive

c)

It works well with variable illumination

d)

It assumes the histogram is bimodal

9.

What is the result of multithresholding?

a)

A color image

b)

A binary image

c)

A grayscale image

d)

An image with multiple gray levels

10.

What is the main challenge in achieving complete segmentation of complex scenes?

a)

High computational cost

b)

Ambiguity in image data

c)

Lack of available algorithms

d)

Insufficient image resolution