Computer Vision Class 10 Questions and Answers

These Class 10 AI Important Questions Chapter 5 Computer Vision Class 10 Important Questions and Answers NCERT Solutions Pdf help in building a strong foundation in artificial intelligence.

Computer Vision Class 10 Important Questions

Class 10 AI Computer Vision Important Questions

Important Questions of Computer Vision Class 10 – Class 10 Computer Vision Important Questions

Computer Vision Class 10 Subjective Questions

Go to this online link https://www.w3schools.com /colors/colors rgb.asp. On the basis of this online tool, try and answer all the below mentioned questions.

Question 1.
What is the output colour when you put R = G = B = 255 ?
Answer:
For the RGB color model, When R=255, G=255, and B=255, the output color is white.

Question 2.
What is the output colour when you put R=G=B=0 ?
Answer:
When you set R( Red )=0, G( Green )=0, and B( Blue )= 0 , the output color is black. In the RGB color model, (0,0, 0 ) represents the absence of light, resulting in black.

Question 3.
How does the colour vary when you put either of the three as 0 and then keep on varying the other two?
Answer:
Red = 0, vary Green and Blue:
Colors will range from black to various shades of cyan (turquoise-like colors).
Example: (0,255,255) is cyan, (0,0,0) is black, (0,128, 128) is a darker cyan.

Green = 0, vary Red and Blue:
Colors will range from black to various shades of magenta and purple.
Example: (255,0,255) is magenta, (0,0,0) is black, (128, 0,128 ) is a darker purple.

Blue = 0, vary Red and Green:
Colors will range from black to various shades of yellow and green.
Example: (255,255,0) is yellow, (0,0,0) is black, (128, 128,0) is olive.

Question 4.
How does the output colour change when all the three colours are varied in same proportion?
Answer:When the RGB (Red, Green, Blue) values are varied equally, the resulting color moves along a gradient from black to white through shades of gray. This means that increasing all three values equally will make the color lighter, while decreasing them will make the color darker, without changing the hue. For example: (0,0,0) is black.
(128,128,128) is a medium gray.
(255,255,255) is white.

Question 5.
What is the RGB value of your favouite colour from the colour palette?
Answer:
The RGB value of light blue is (173,216,230).

Question 6.
What is a Kernel?
Answer:
A Kernel is a matrix, which is slid across the image and multiplied with the input such that the output is enhanced in a certain desirable manner. Each kernel has a different value for different kind of effects that we want to apply to an image.

Question 7.
What is a Neural Network?
Answer:
A Neural Network is a computational model inspired by the way biological neural networks in the brain process information. It consists of interconnected nodes (neurons) arranged in layers.
The three main layers are:

1. Input Layer Receives the initial data or features to be processed.
2. Hidden Layer Performs computations and feature extraction; there can be multiple hidden layers.
3. Output Layer Produces the final prediction or classification result.

Each neuron in a layer is connected to neurons in the next layer, with weights that are adjusted during training to minimize error and improve accuracy.

Computer Vision Class 10 Very Short Answer Type Questions

Question 1.
It is basically the dimensions through which you can measure how many pixels are there on a screen. What is it?
Answer:
Resolution

Question 2.
What is the process of detecting an instance of the object, categorising it and giving each pixel a label on that basis?
Answer:
Instance segmentation

Question 3.
With reference to AI domain, expand the term CV.
Answer:
CV stands for Computer Vision.

Question 4.
Which app uses face filters?
Answer:
Snapchat uses face filters.

Question 5.
Give an example of object recognition.
Answer:
Object recognition is identifying specific instances of objects and associating them with known categories or concepts.

Question 6.
Mention any 2 features of image based on which they are characterised.
Answer:
Two features based on which images are characterised are – textures and edges.

Question 7.
How many channels does a color image have?
Answer:
Three channels

Question 8.
What is a kernel?
Ans.
A kernel, is a small matrix of numerical values that defines a specific operation to be performed on the input image.

Question 9.
What is OpenCV?
Answer:
OpenCV is an open-source computer vision and machine learning software library that provides various tools and functions for image and video processing.

Computer Vision Class 10 Short Answer Type Questions

Question 1.
Name the four important layers in CNN.
Ans.
The 4 layers in CNN are:

1. Convolution layer
2. Rectified linear unit
3. Pooling layer
4. Fully connected layer

Question 2.
Differentiate between Max pooling and Average pooling.
Answer:
The difference between max pooling and average pooling is:
Max pooling is the most commonly used method that selects the maximum value of the current image view and helps preserve the maximum detected features.

While, Average pooling finds out the average value of the current image view and thus down samples the feature map.

Question 3.
Name the real-life applications of computer vision.
Answer:
The real-life applications of computer vision are:

• Facial recognition in smartphones
• Face filters
• Google translate app

Question 4.
How does the computer see an image?
Ans.
In a digital image, every coloured image that is stored can be split into 3 different channels, i.e. Red (R), Green (G) and Blue (B), with different intensities. The computer identifies the value related to each pixel and determines the size and colour of the image.

Question 5.
How computer vision is helping in medical imaging?
Answer:
Computer vision plays a pivotal role in medical imaging, facilitating tasks such as image analysis, diagnosis, treatment planning, and surgical guidance across various medical specialties. By analysing medical images, including X-rays, CT scans, MRIs, and ultrasound images, computer vision algorithms assist healthcare professionals in detecting abnormalities, quantifying disease progression, identifying anatomical structures, and guiding interventions.

Question 6.
How Google translate uses computer vision?
Answer:
Google Translate employs computer vision to enable instant translation of text captured through a smartphone camera. Using optical character recognition (OCR) technology, the app recognises and extracts text from images, such as signs, menus, or documents. Then, machine translation algorithms process the extracted text to provide translations in real-time, facilitating communication across languages.

Question 7.
Explain the term resolution with an example.
Answer:
Resolution of an image refers to the number of pixels in an image, across the width and height. For example a monitor resolution of 1280 × 1024. This means there are 1280 pixels from one side to the other, and 1024 pixels from top to bottom.

Question 8.
Face lock feature of a smartphone is an example of computer vision. Briefly discuss this feature.
Answer:
The face lock feature of a smartphone is indeed an example of computer vision technology in action. It utilises the device’s front-facing camera and sophisticated algorithms to recognise and authenticate the user’s face before granting access to the device.

Question 9.
Can you define “digital image”?
Answer:
A digital image is a picture that’s made up of smaller parts, called pixels. These pixels are made of numerical components that represent their color codes and intensity. AI systems us these numbers to understand an image.

Question 10.
Differentiate between grayscale and RGB images.
Answer:
Differentiate between grayscale and RGB images are as follows

Question 11.
What’s the purpose of grayscaling?
Answer:
Grayscale is the range of whiteness to blackness of a digital image. Programmers take an image that’s in color and change it to grayscale, which is called grayscaling. This helps simplify the image data so a computer can more easily process the input.

Question 12.
What programming languages does computer vision support?
Answer:
Computer vision can use programming languages such * as Java, C/C++, Prolog, Python and LISP. I’ve primarily used Java in past projects, but I hàve certification in Prolog as well and basic understanding of the others.

Computer Vision Class 10 Long Answer Type Questions

Question 1.
Explain the different layers of convolution neural network.
Answer:
Refer to text on page 136-137 (Layers of CNN)

Question 2.
Define the computer vision task.
Answer:
Refer to text on page 134 (Computer vision tasks)

Question 3.
What is image? Also, Explain the basics of image.
Answer:
Image is a visual representation of an object, a scene or a concept.
Basics of image Refer to text on page 134-135 (Basics of images)

Computer Vision Class 10 Activities

Activity

Imagine that your security camera is capturing an image. At the top of the image, we are given six small patches of image. Take a pencil and mark the exact location of those patches in the image.

(a) Were you able to find the exact location of all the patches?
(b) Which one was the most difficult to find?
(c) Which one was the easiest to find?

Conclusion The unique features of the images are the easiest to find, it may the corners, start of the image or the end points of the image.

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