CBSE Textbook: Computer Vision - Class 10 PDF Download

 Page 2


 
    
 
 
      
 
              
 
     
 
          
        
   
  
 
          
 
  
        
 
    
           
   
          
      
         
 
 
 
  
 
 
 
 
 
 
* Emoji Scavenger Hunt: https://emojiscavengerhunt.withgoogle.com/ 
 
 
Go to the link and try to play the game Emoji Scavenger Hunt. The challenge here is to find 8 items 
within the time limit to pass. Did you manage to win? 
            What was the strategy that you applied to win this game? 
            Was the computer able to identify all the items you brought in front of it? 
            Did the lighting of the room affect the identifying of items by the machine? 
       
         A Quick Overview of Computer Vision! 
Computer vision is the process of extraction of information from images, text, videos, etc. 
A system that can process, analyze and make sense of visual data in the same way as humans do. 
 
 
Elephant 
Human Vision System 
 
 
Brain 
 
 
 
Eye 
Sensing 
Device 
Interpreting Device 
Page 3


 
    
 
 
      
 
              
 
     
 
          
        
   
  
 
          
 
  
        
 
    
           
   
          
      
         
 
 
 
  
 
 
 
 
 
 
* Emoji Scavenger Hunt: https://emojiscavengerhunt.withgoogle.com/ 
 
 
Go to the link and try to play the game Emoji Scavenger Hunt. The challenge here is to find 8 items 
within the time limit to pass. Did you manage to win? 
            What was the strategy that you applied to win this game? 
            Was the computer able to identify all the items you brought in front of it? 
            Did the lighting of the room affect the identifying of items by the machine? 
       
         A Quick Overview of Computer Vision! 
Computer vision is the process of extraction of information from images, text, videos, etc. 
A system that can process, analyze and make sense of visual data in the same way as humans do. 
 
 
Elephant 
Human Vision System 
 
 
Brain 
 
 
 
Eye 
Sensing 
Device 
Interpreting Device 
 
 
Computer Vision and Artificial Intelligence 
Computer vision is a field of artificial intelligence (AI). 
AI enables computers to think, and computer vision enables AI to see, observe and make sense 
of visual data (like images & videos). 
 
Computer Vision Vs. Image Processing 
Computer Vision Image Processing 
• Computer vision deals with extracting 
information from the input images or 
videos to infer meaningful information and 
understanding them to predict the visual 
input 
• Computer Vision is a superset of 
Image Processing. 
• Examples - Object detection, 
Handwriting recognition, etc. 
• Image processing is mainly focused on 
processing the raw input images to 
enhance them or preparing them to do 
other tasks 
• Image Processing is a subset of 
Computer Vision. 
• Examples - Rescaling image, Correcting 
brightness, Changing tones, etc. 
 
5.1 Applications of Computer Vision 
The concept of computer vision was first introduced in the 1970s. All these new 
applications of computer vision excited everyone. Having said that, computer vision 
technology advanced enough to make these applications available to everyone at ease 
today. However, in recent years the world witnessed a significant leap in technology that 
has put computer vision on the priority list of many industries. Let us look at some of 
them: 
 
 
 
 
 
 
 
 
 
Artificial Intelligence 
Computer 
Vision 
Deep 
Learnin
g 
Machine 
Learning 
Facial Recognition*: With the advent of smart cities and 
smart homes, Computer Vision plays a vital role in making the 
home smarter. Security being the most important application 
involves the use of Computer Vision for facial recognition. It 
can be either guest recognition or log maintenance of the 
visitors. It also finds its application in schools for an 
attendance system based on facial recognition of students. 
 
Page 4


 
    
 
 
      
 
              
 
     
 
          
        
   
  
 
          
 
  
        
 
    
           
   
          
      
         
 
 
 
  
 
 
 
 
 
 
* Emoji Scavenger Hunt: https://emojiscavengerhunt.withgoogle.com/ 
 
 
Go to the link and try to play the game Emoji Scavenger Hunt. The challenge here is to find 8 items 
within the time limit to pass. Did you manage to win? 
            What was the strategy that you applied to win this game? 
            Was the computer able to identify all the items you brought in front of it? 
            Did the lighting of the room affect the identifying of items by the machine? 
       
         A Quick Overview of Computer Vision! 
Computer vision is the process of extraction of information from images, text, videos, etc. 
A system that can process, analyze and make sense of visual data in the same way as humans do. 
 
 
Elephant 
Human Vision System 
 
 
Brain 
 
 
 
Eye 
Sensing 
Device 
Interpreting Device 
 
 
Computer Vision and Artificial Intelligence 
Computer vision is a field of artificial intelligence (AI). 
AI enables computers to think, and computer vision enables AI to see, observe and make sense 
of visual data (like images & videos). 
 
Computer Vision Vs. Image Processing 
Computer Vision Image Processing 
• Computer vision deals with extracting 
information from the input images or 
videos to infer meaningful information and 
understanding them to predict the visual 
input 
• Computer Vision is a superset of 
Image Processing. 
• Examples - Object detection, 
Handwriting recognition, etc. 
• Image processing is mainly focused on 
processing the raw input images to 
enhance them or preparing them to do 
other tasks 
• Image Processing is a subset of 
Computer Vision. 
• Examples - Rescaling image, Correcting 
brightness, Changing tones, etc. 
 
5.1 Applications of Computer Vision 
The concept of computer vision was first introduced in the 1970s. All these new 
applications of computer vision excited everyone. Having said that, computer vision 
technology advanced enough to make these applications available to everyone at ease 
today. However, in recent years the world witnessed a significant leap in technology that 
has put computer vision on the priority list of many industries. Let us look at some of 
them: 
 
 
 
 
 
 
 
 
 
Artificial Intelligence 
Computer 
Vision 
Deep 
Learnin
g 
Machine 
Learning 
Facial Recognition*: With the advent of smart cities and 
smart homes, Computer Vision plays a vital role in making the 
home smarter. Security being the most important application 
involves the use of Computer Vision for facial recognition. It 
can be either guest recognition or log maintenance of the 
visitors. It also finds its application in schools for an 
attendance system based on facial recognition of students. 
 
 
 
Face Filters*: Modern-day apps like lnstagram and Snapchat 
have a lot of features based on the  
usage of computer vision. The application of face filters is one 
among them. Through the camera, the machine or the 
algorithm is able to identify the facial dynamics of the person 
and applies the facial filter selected. 
 
Google's Search by Image*: The maximum 
amount of searching for data on Google's search 
engine comes from textual data, but at the same 
time it has an interesting feature of getting 
search results through an image. This uses 
Computer Vision as it compares different 
features of the input image to the database of 
images and gives us the search result while at the 
same time analysing various features of the 
image. 
 
Computer Vision in Retail*: The retail field has been one 
of the fastest-growing fields and at the same time is using 
Computer Vision for making the user experience more 
fruitful. Retailers can use Computer Vision techniques to 
track customers' movements through stores, analyse 
navigational routes and detect walking patterns. 
 
 
 
Inventory Management is another such application. 
Through security camera image analysis, a Computer 
Vision algorithm can generate a very accurate estimate of 
the items available in the store. Also, it can analyse the 
use of shelf space to identify suboptimal configurations 
and suggest better item placement. 
 
 
 
Self-Driving Cars: Computer Vision is the 
fundamental technology behind the 
development of autonomous vehicles. Most 
leading car manufacturers in the world are 
reaping the benefits of investing in artificial 
intelligence for developing on-road versions of 
hands-free technology. This involves the process 
of identifying the objects, getting navigational 
routes and also at the same time environment 
monitoring. 
 
 
Page 5


 
    
 
 
      
 
              
 
     
 
          
        
   
  
 
          
 
  
        
 
    
           
   
          
      
         
 
 
 
  
 
 
 
 
 
 
* Emoji Scavenger Hunt: https://emojiscavengerhunt.withgoogle.com/ 
 
 
Go to the link and try to play the game Emoji Scavenger Hunt. The challenge here is to find 8 items 
within the time limit to pass. Did you manage to win? 
            What was the strategy that you applied to win this game? 
            Was the computer able to identify all the items you brought in front of it? 
            Did the lighting of the room affect the identifying of items by the machine? 
       
         A Quick Overview of Computer Vision! 
Computer vision is the process of extraction of information from images, text, videos, etc. 
A system that can process, analyze and make sense of visual data in the same way as humans do. 
 
 
Elephant 
Human Vision System 
 
 
Brain 
 
 
 
Eye 
Sensing 
Device 
Interpreting Device 
 
 
Computer Vision and Artificial Intelligence 
Computer vision is a field of artificial intelligence (AI). 
AI enables computers to think, and computer vision enables AI to see, observe and make sense 
of visual data (like images & videos). 
 
Computer Vision Vs. Image Processing 
Computer Vision Image Processing 
• Computer vision deals with extracting 
information from the input images or 
videos to infer meaningful information and 
understanding them to predict the visual 
input 
• Computer Vision is a superset of 
Image Processing. 
• Examples - Object detection, 
Handwriting recognition, etc. 
• Image processing is mainly focused on 
processing the raw input images to 
enhance them or preparing them to do 
other tasks 
• Image Processing is a subset of 
Computer Vision. 
• Examples - Rescaling image, Correcting 
brightness, Changing tones, etc. 
 
5.1 Applications of Computer Vision 
The concept of computer vision was first introduced in the 1970s. All these new 
applications of computer vision excited everyone. Having said that, computer vision 
technology advanced enough to make these applications available to everyone at ease 
today. However, in recent years the world witnessed a significant leap in technology that 
has put computer vision on the priority list of many industries. Let us look at some of 
them: 
 
 
 
 
 
 
 
 
 
Artificial Intelligence 
Computer 
Vision 
Deep 
Learnin
g 
Machine 
Learning 
Facial Recognition*: With the advent of smart cities and 
smart homes, Computer Vision plays a vital role in making the 
home smarter. Security being the most important application 
involves the use of Computer Vision for facial recognition. It 
can be either guest recognition or log maintenance of the 
visitors. It also finds its application in schools for an 
attendance system based on facial recognition of students. 
 
 
 
Face Filters*: Modern-day apps like lnstagram and Snapchat 
have a lot of features based on the  
usage of computer vision. The application of face filters is one 
among them. Through the camera, the machine or the 
algorithm is able to identify the facial dynamics of the person 
and applies the facial filter selected. 
 
Google's Search by Image*: The maximum 
amount of searching for data on Google's search 
engine comes from textual data, but at the same 
time it has an interesting feature of getting 
search results through an image. This uses 
Computer Vision as it compares different 
features of the input image to the database of 
images and gives us the search result while at the 
same time analysing various features of the 
image. 
 
Computer Vision in Retail*: The retail field has been one 
of the fastest-growing fields and at the same time is using 
Computer Vision for making the user experience more 
fruitful. Retailers can use Computer Vision techniques to 
track customers' movements through stores, analyse 
navigational routes and detect walking patterns. 
 
 
 
Inventory Management is another such application. 
Through security camera image analysis, a Computer 
Vision algorithm can generate a very accurate estimate of 
the items available in the store. Also, it can analyse the 
use of shelf space to identify suboptimal configurations 
and suggest better item placement. 
 
 
 
Self-Driving Cars: Computer Vision is the 
fundamental technology behind the 
development of autonomous vehicles. Most 
leading car manufacturers in the world are 
reaping the benefits of investing in artificial 
intelligence for developing on-road versions of 
hands-free technology. This involves the process 
of identifying the objects, getting navigational 
routes and also at the same time environment 
monitoring. 
 
 
 
 
 Medical Imaging*: For the last decades, 
computer supported medical imaging 
application has been a trustworthy help for 
physicians. It doesn't only create and analyse 
images, but also becomes an assistant and 
helps doctors with their interpretation. The 
application is used to read and convert 20 scan 
images into interactive 30 models that enable 
medical professionals to gain a detailed 
understanding of a patient's health condition.   
 
 
 
 
Google Translate App*: All you need to do to read signs in a 
foreign language is to point your phone's camera at the 
words and let the Google Translate app tell you what it 
means in your preferred language almost instantly. By using 
optical character recognition to see the image and 
augmented reality to overlay an accurate translation, this is 
a convenient tool that uses Computer Vision 
 
 
 
 
 
5.2 Computer Vision Tasks 
 
The various applications of Computer Vision are based on a certain number of tasks that are 
performed to get certain information from the input image which can be directly used for 
prediction or forms the base for further analysis. The tasks used in a computer vision application are: 
 
 
 
 
 
Objects 
 
Objects 
Detection