Master Image Processing Techniques in Computer Graphics | Online Quizzes

Question 1

Identify the choice that is not among the essential steps involved in digital image processing.

Accepted Answer

Finding and tracking objects within the image

Answer

Capturing the image

Answer

Enhancing the image

Answer

Restoring the image

Question 2

In spatial filtering, pixel values in an image are altered using information from:

Accepted Answer

Only neighboring pixels

Answer

Histogram of the entire image

Answer

Statistical characteristics of the image

Answer

None of the listed options

Question 3

Which of the following image processing techniques operates in the frequency domain?

Accepted Answer

Fourier transform

Answer

Histogram equalization

Answer

Convolution

Answer

Median filtering

Question 4

Image segmentation is primarily concerned with:

Accepted Answer

Dividing an image into distinct regions

Answer

Improving the contrast of an image

Answer

Removing noise from an image

Answer

Detecting entities within an image

Question 5

What is the primary purpose of histogram equalization in image processing?

Accepted Answer

To improve the contrast of an image

Answer

To reduce noise in an image

Answer

To transform an image to the frequency domain

Answer

To remove artifacts from an image

Question 6

What is the fundamental distinction between spatial and frequency domain image processing?

Accepted Answer

Spatial domain processing operates on individual pixels, while frequency domain processing operates on the Fourier transform of the image

Answer

Frequency domain processing is computationally faster than spatial domain processing

Answer

Spatial domain processing is exclusively used for image enhancement, while frequency domain processing is used for image restoration

Answer

There is no significant difference between spatial and frequency domain image processing

Question 7

Which of the following is a key advantage of using JPEG compression in image processing?

Accepted Answer

High compression ratio

Answer

Lossless compression

Answer

Fast decompression time

Answer

Preserves image quality without any loss

Question 8

What is the primary function of the Hough transform in image processing?

Accepted Answer

To detect lines and circles in an image

Answer

To reduce noise in an image

Answer

To compress an image

Answer

To enhance the contrast of an image

Question 9

Which of the following image segmentation techniques relies on the concept of region growing?

Accepted Answer

Region growing

Answer

Thresholding

Answer

Clustering

Answer

Watershed segmentation

Question 10

What is the intended purpose of applying a morphological dilation operation in image processing?

Accepted Answer

To enlarge objects in an image

Answer

To reduce noise in an image

Answer

To detect edges in an image

Answer

To segment an image

Question 11

What is the significance of the Nyquist-Shannon sampling theorem in the context of image processing?

Accepted Answer

It determines the maximum sampling frequency to avoid aliasing

Answer

It defines the resolution of an image

Answer

It establishes a relationship between the spatial and frequency domains

Answer

It determines the number of colors in an image

Question 12

Which initial step is crucial in the sequence of image processing algorithms?

Accepted Answer

Acquiring the image

Answer

Enhancing the image

Answer

Analyzing the image

Answer

Visualizing the image

Question 13

What is the primary goal of image segmentation in image processing?

Accepted Answer

Partitioning an image into distinct regions

Answer

Adjusting image brightness and contrast

Answer

Removing noise from an image

Answer

Compressing an image with no data loss

Question 14

Which image processing operator is specifically designed to enhance edges in an image?

Accepted Answer

Convolution

Answer

Thresholding

Answer

Histogram equalization

Answer

Fourier transform

Question 15

What is the primary purpose of histogram equalization in image processing?

Accepted Answer

Adjusting image brightness and contrast

Answer

Enhancing image edges

Answer

Reducing image noise

Answer

Transforming an image into the frequency domain

Question 16

What is the key advantage of utilizing a discrete Fourier transform in image processing?

Accepted Answer

Converting the image into the frequency domain

Answer

Enhancing image edges

Answer

Reducing image noise

Answer

Compressing an image without data loss

Question 17

Differentiate between spatial domain and frequency domain in the context of image processing.

Accepted Answer

Spatial domain operates directly on image pixels, while frequency domain operates on the transformed image

Answer

Frequency domain operates directly on image pixels, while spatial domain operates on the transformed image

Answer

Spatial domain is exclusive to image enhancement, while frequency domain is exclusive to image compression

Answer

Frequency domain is exclusive to image enhancement, while spatial domain is exclusive to image compression

Question 18

Which technique is commonly used to improve the contrast in an image?

Accepted Answer

Histogram equalization

Answer

Edge detection

Answer

Image segmentation

Answer

Image classification

Question 19

What is the purpose of applying a Gaussian filter to an image?

Accepted Answer

Reducing noise

Answer

Sharpening edges

Answer

Extract features

Answer

Detect objects

Question 20

Which color model is most commonly used to represent digital images?

Accepted Answer

RGB

Answer

HSV

Answer

YIQ

Answer

CMYK

Question 21

What is the main advantage of using a Canny edge detector over a Sobel edge detector?

Accepted Answer

Improved noise immunity

Answer

More accurate edge detection

Answer

Faster computation

Answer

Simplicity of implementation

Question 22

What is the significance of the Hough transform in image processing?

Accepted Answer

Detecting lines and curves

Answer

Transforming images between different coordinate systems

Answer

Enhancing images for visualization

Answer

Compressing images for storage

Question 23

Which of the following is NOT a consideration when choosing an image compression algorithm?

Accepted Answer

Availability of hardware acceleration

Answer

Image quality

Answer

Compression ratio

Answer

Processing time

Question 24

What is a key difference between supervised and unsupervised image segmentation?

Accepted Answer

Supervised requires labeled training data, while unsupervised does not

Answer

Unsupervised is faster than supervised

Answer

Supervised is more accurate than unsupervised

Answer

Unsupervised is more suitable for small datasets

Question 25

In computer graphics, which noise reduction technique is commonly used for digital image processing?

Accepted Answer

Median filtering

Answer

Histogram equalization

Answer

Convolution

Answer

Edge detection

Question 26

In image processing, which technique is specifically used to enhance edges and details?

Accepted Answer

Unsharp Masking

Answer

Histogram Equalization

Answer

Median Filtering

Answer

Binarization

Question 27

Which image enhancement technique enhances contrast and dynamic range by adjusting pixel value distribution?

Accepted Answer

Histogram equalization

Answer

Image segmentation

Answer

Image denoising

Answer

Object detection

Question 28

What is the primary purpose of histogram equalization?

Accepted Answer

To improve image contrast

Answer

To reduce image noise

Answer

To sharpen image edges

Answer

To remove image artifacts

Question 29

What is the fundamental difference between lossy and lossless image compression?

Accepted Answer

Lossy compression permanently removes data, while lossless compression retains all original data.

Answer

Lossy compression results in smaller file sizes, while lossless compression produces larger files.

Answer

Lossy compression is reversible, while lossless compression is irreversible.

Answer

Lossy compression is commonly used for medical images, while lossless compression is used for digital photographs.

Question 30

Which of the following image segmentation techniques is based on the region growing approach?

Accepted Answer

Region growing

Answer

K-means clustering

Answer

Watershed segmentation

Answer

Boundary detection

Question 31

What is the primary application of the Fourier transform in image processing?

Accepted Answer

To analyze the frequency content of images

Answer

To detect edges in images

Answer

To enhance the contrast of images

Answer

To remove noise from images

Question 32

What is a key advantage of using convolutional neural networks for image classification?

Accepted Answer

They can learn complex relationships within images.

Answer

They require minimal preprocessing.

Answer

They are robust to noise.

Answer

They are computationally very efficient.

Question 33

Identify the operation that does not fall under the umbrella of fundamental image processing:

Accepted Answer

Data visualization

Answer

Filtering

Answer

Segmentation

Answer

Color correction

Question 34

What is the primary purpose of applying a Gaussian filter to an image?

Accepted Answer

Blurring the image to reduce noise and enhance clarity

Answer

Detecting edges within the image

Answer

Sharpening the image to enhance details

Answer

Compressing the image to reduce file size

Question 35

Which color space is predominantly used in the field of computer graphics for image representation?

Accepted Answer

RGB

Answer

CMYK

Answer

HSL

Answer

YCbCr

Question 36

What is the fundamental objective of image segmentation in image processing?

Accepted Answer

Partitioning an image into distinct regions based on specific characteristics

Answer

Adjusting an image's brightness levels to enhance visibility

Answer

Eliminating noise and artifacts from an image

Answer

Reducing an image's file size for efficient storage

Question 37

Among the listed image processing techniques, which one is specifically employed for detecting objects within an image?

Accepted Answer

Template matching

Answer

Histogram equalization

Answer

Median filtering

Answer

Principal component analysis

Question 38

Differentiate between image enhancement and image restoration in terms of their objectives:

Accepted Answer

Enhancement aims to improve the visual appeal of an image, while restoration focuses on correcting distortions.

Answer

Restoration enhances images, while enhancement corrects distortions.

Answer

Both enhancement and restoration solely aim to improve an image's visual appeal.

Answer

Neither enhancement nor restoration has any impact on an image's appearance.

Question 39

Which of the following image compression techniques involves irreversible data loss?

Accepted Answer

JPEG

Answer

PNG

Answer

TIFF

Answer

BMP

Question 40

What is the primary goal of image registration in image processing?

Accepted Answer

Aligning multiple images of the same scene

Answer

Compressing images to minimize storage requirements

Answer

Eliminating noise and artifacts from images

Answer

Segmenting images into distinct regions

Question 41

Which of the listed factors does not pose a significant challenge in the field of image processing?

Accepted Answer

Interpreting the semantic content of images

Answer

Effectively handling noise within images

Answer

Processing large volumes of image data efficiently

Answer

Achieving real-time performance for image processing tasks

Question 42

What is the main purpose of applying histogram equalization to an image?

Accepted Answer

Adjusting the distribution of pixel intensities to enhance contrast

Answer

Removing noise and artifacts from the image

Answer

Sharpening edges and enhancing image details

Answer

Reducing the image size for efficient storage and transfer

Question 43

Which type of filter is primarily used to smoothen an image by blurring out noise and high-frequency details?

Accepted Answer

Low-pass filter

Answer

High-pass filter

Answer

Median filter

Answer

Sobel filter

Question 44

What is the key difference between lossless and lossy image compression techniques?

Accepted Answer

Lossless compression retains all the original image data, while lossy compression discards some information for better compression.

Answer

Lossy compression retains all the original image data, while lossless compression discards some information for better compression.

Answer

Lossless compression is faster than lossy compression.

Answer

Lossy compression is always better than lossless compression.

Question 45

Which of the following is NOT considered a major application domain for image processing techniques?

Accepted Answer

Text processing and document analysis

Answer

Medical imaging and analysis

Answer

Remote sensing and satellite imagery

Answer

Computer vision and object recognition

Question 46

Edge detection is a crucial technique in image processing. What is its primary purpose?

Accepted Answer

Identifying the boundaries and structures within an image

Answer

Enhancing the overall brightness and contrast of an image

Answer

Removing noise and unwanted artifacts from an image

Answer

Compressing an image to reduce its file size

Question 47

Color spaces play a significant role in image processing. What is their primary purpose?

Accepted Answer

Representing colors in various formats and models to facilitate image analysis and manipulation.

Answer

Enhancing the visual quality and aesthetic appeal of images.

Answer

Reducing the computational complexity of image processing operations.

Answer

Compressing images for efficient storage and transmission.

Question 48

In image processing, what does a histogram visually represent?

Accepted Answer

The distribution of pixel intensity values in an image.

Answer

The image's resolution, measured in pixels per inch.

Answer

The average brightness value of all pixels in an image.

Answer

The total number of pixels in an image.

Question 49

What is the primary purpose of morphological operations in image processing?

Accepted Answer

To analyze and modify the shape and structure of objects within an image.

Answer

To remove unwanted noise and artifacts from an image.

Answer

To reduce the file size of an image by removing redundant information.

Answer

To detect edges and boundaries within an image.

Question 50

What is the fundamental concept behind edge detection in image processing?

Accepted Answer

Identifying abrupt changes in pixel intensity values, indicating boundaries between objects or regions.

Answer

Smoothing out sharp edges and reducing noise in an image.

Answer

Adjusting the color balance of an image to enhance its visual appeal.

Answer

Removing random noise from an image to improve its clarity.

Question 51

Which of the following techniques operates in the frequency domain for image processing?

Accepted Answer

Fourier transform.

Answer

Histogram equalization, which adjusts the distribution of pixel intensities.

Answer

Convolution, a spatial domain operation used for filtering and edge detection.

Answer

Erosion, a morphological operation that shrinks objects in an image.

Question 52

What is the primary objective of feature extraction in image processing?

Accepted Answer

To identify and extract meaningful features or characteristics from an image that represent its content.

Answer

To enhance the contrast of an image to make features more visible.

Answer

To remove unwanted noise and artifacts that can obscure important information.

Question 53

Which of these is a significant advantage of utilizing deep learning for image processing tasks?

Accepted Answer

Deep learning models can learn complex, hierarchical representations of image data, allowing them to understand intricate patterns.

Answer

Deep learning models generally require significantly less data compared to traditional machine learning methods.

Answer

Deep learning models are known for their exceptionally fast processing speeds, making them ideal for real-time applications.

Answer

Deep learning models often produce highly interpretable results, making it easy to understand their decision-making process.