Computer Vision | Artificial Intelligence for Class 10 PDF Download

 Page 1


 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Computer Vision 
Introduction  
In the previous chapter, you studied the concepts of Artificial Intelligence for Data Sciences. It is a 
concept to unify statistics, data analysis, machine learning and their related methods in order to 
understand and analyse actual phenomena with data.  
As we all know, artificial intelligence is a technique that enables computers to mimic human 
intelligence. As humans we can see things, analyse it and then do the required action on the basis of 
what we see.  
But can machines do the same? Can machines have the eyes that humans have? If you answered Yes, 
then you are absolutely right. The Computer Vision domain of Artificial Intelligence, enables machines 
to see through images or visual data, process and analyse them on the basis of algorithms and 
methods in order to analyse actual phenomena with images.  
Now before we get into the concepts of Computer Vision, let us experience this domain with the help 
of the following game: 
* Emoji Scavenger Hunt  : 
https://emojiscavengerhunt.withgoogle.com/ 
 
 
Go to the link and try to play the game of 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? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
  
Page 2


 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Computer Vision 
Introduction  
In the previous chapter, you studied the concepts of Artificial Intelligence for Data Sciences. It is a 
concept to unify statistics, data analysis, machine learning and their related methods in order to 
understand and analyse actual phenomena with data.  
As we all know, artificial intelligence is a technique that enables computers to mimic human 
intelligence. As humans we can see things, analyse it and then do the required action on the basis of 
what we see.  
But can machines do the same? Can machines have the eyes that humans have? If you answered Yes, 
then you are absolutely right. The Computer Vision domain of Artificial Intelligence, enables machines 
to see through images or visual data, process and analyse them on the basis of algorithms and 
methods in order to analyse actual phenomena with images.  
Now before we get into the concepts of Computer Vision, let us experience this domain with the help 
of the following game: 
* Emoji Scavenger Hunt  : 
https://emojiscavengerhunt.withgoogle.com/ 
 
 
Go to the link and try to play the game of 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? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
  
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Did the lighting of the room affect the identifying of items by the machine? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
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, the 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: 
 
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 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*: The modern-day apps like Instagram 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 give us the search result while at the 
same time analysing various features of the image.  
  
Page 3


 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Computer Vision 
Introduction  
In the previous chapter, you studied the concepts of Artificial Intelligence for Data Sciences. It is a 
concept to unify statistics, data analysis, machine learning and their related methods in order to 
understand and analyse actual phenomena with data.  
As we all know, artificial intelligence is a technique that enables computers to mimic human 
intelligence. As humans we can see things, analyse it and then do the required action on the basis of 
what we see.  
But can machines do the same? Can machines have the eyes that humans have? If you answered Yes, 
then you are absolutely right. The Computer Vision domain of Artificial Intelligence, enables machines 
to see through images or visual data, process and analyse them on the basis of algorithms and 
methods in order to analyse actual phenomena with images.  
Now before we get into the concepts of Computer Vision, let us experience this domain with the help 
of the following game: 
* Emoji Scavenger Hunt  : 
https://emojiscavengerhunt.withgoogle.com/ 
 
 
Go to the link and try to play the game of 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? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
  
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Did the lighting of the room affect the identifying of items by the machine? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
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, the 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: 
 
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 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*: The modern-day apps like Instagram 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 give us the search result while at the 
same time analysing various features of the image.  
  
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Computer Vision in Retail*: The retail field has been one of the 
fastest growing field 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 developing 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 2D scan 
images into interactive 3D 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.  
 
  
Page 4


 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Computer Vision 
Introduction  
In the previous chapter, you studied the concepts of Artificial Intelligence for Data Sciences. It is a 
concept to unify statistics, data analysis, machine learning and their related methods in order to 
understand and analyse actual phenomena with data.  
As we all know, artificial intelligence is a technique that enables computers to mimic human 
intelligence. As humans we can see things, analyse it and then do the required action on the basis of 
what we see.  
But can machines do the same? Can machines have the eyes that humans have? If you answered Yes, 
then you are absolutely right. The Computer Vision domain of Artificial Intelligence, enables machines 
to see through images or visual data, process and analyse them on the basis of algorithms and 
methods in order to analyse actual phenomena with images.  
Now before we get into the concepts of Computer Vision, let us experience this domain with the help 
of the following game: 
* Emoji Scavenger Hunt  : 
https://emojiscavengerhunt.withgoogle.com/ 
 
 
Go to the link and try to play the game of 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? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
  
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Did the lighting of the room affect the identifying of items by the machine? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
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, the 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: 
 
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 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*: The modern-day apps like Instagram 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 give us the search result while at the 
same time analysing various features of the image.  
  
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Computer Vision in Retail*: The retail field has been one of the 
fastest growing field 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 developing 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 2D scan 
images into interactive 3D 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.  
 
  
 
 
Computer Vision: Getting Started 
Computer Vision is a domain of Artificial Intelligence, that deals with the images. It involves the 
concepts of image processing and machine learning models to build a Computer Vision based 
application.  
Computer Vision Tasks 
The various applications of Computer Vision are based on a certain number of tasks which 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 : 
 
Classification 
Image Classification problem is the task of assigning an input image one label from a fixed set of 
categories. This is one of the core problems in CV that, despite its simplicity, has a large variety of 
practical applications.  
Classification + Localisation  
This is the task which involves both processes of identifying what object is present in the image and 
at the same time identifying at what location that object is present in that image. It is used only for 
single objects.   
Object Detection  
Object detection is the process of finding instances of real-world objects such as faces, bicycles, and 
buildings in images or videos. Object detection algorithms typically use extracted features and 
learning algorithms to recognize instances of an object category. It is commonly used in applications 
such as image retrieval and automated vehicle parking systems. 
Instance Segmentation 
Instance Segmentation is the process of detecting instances of the objects, giving them a category and 
then giving each pixel a label on the basis of that. A segmentation algorithm takes an image as input 
and outputs a collection of regions (or segments). 
For Single 
Objects
Classification
Classification + 
Localisation
For Multiple 
Objects
Object 
Detection
Instance 
Segementation
Page 5


 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Computer Vision 
Introduction  
In the previous chapter, you studied the concepts of Artificial Intelligence for Data Sciences. It is a 
concept to unify statistics, data analysis, machine learning and their related methods in order to 
understand and analyse actual phenomena with data.  
As we all know, artificial intelligence is a technique that enables computers to mimic human 
intelligence. As humans we can see things, analyse it and then do the required action on the basis of 
what we see.  
But can machines do the same? Can machines have the eyes that humans have? If you answered Yes, 
then you are absolutely right. The Computer Vision domain of Artificial Intelligence, enables machines 
to see through images or visual data, process and analyse them on the basis of algorithms and 
methods in order to analyse actual phenomena with images.  
Now before we get into the concepts of Computer Vision, let us experience this domain with the help 
of the following game: 
* Emoji Scavenger Hunt  : 
https://emojiscavengerhunt.withgoogle.com/ 
 
 
Go to the link and try to play the game of 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? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
  
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Did the lighting of the room affect the identifying of items by the machine? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
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, the 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: 
 
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 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*: The modern-day apps like Instagram 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 give us the search result while at the 
same time analysing various features of the image.  
  
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
Computer Vision in Retail*: The retail field has been one of the 
fastest growing field 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 developing 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 2D scan 
images into interactive 3D 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.  
 
  
 
 
Computer Vision: Getting Started 
Computer Vision is a domain of Artificial Intelligence, that deals with the images. It involves the 
concepts of image processing and machine learning models to build a Computer Vision based 
application.  
Computer Vision Tasks 
The various applications of Computer Vision are based on a certain number of tasks which 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 : 
 
Classification 
Image Classification problem is the task of assigning an input image one label from a fixed set of 
categories. This is one of the core problems in CV that, despite its simplicity, has a large variety of 
practical applications.  
Classification + Localisation  
This is the task which involves both processes of identifying what object is present in the image and 
at the same time identifying at what location that object is present in that image. It is used only for 
single objects.   
Object Detection  
Object detection is the process of finding instances of real-world objects such as faces, bicycles, and 
buildings in images or videos. Object detection algorithms typically use extracted features and 
learning algorithms to recognize instances of an object category. It is commonly used in applications 
such as image retrieval and automated vehicle parking systems. 
Instance Segmentation 
Instance Segmentation is the process of detecting instances of the objects, giving them a category and 
then giving each pixel a label on the basis of that. A segmentation algorithm takes an image as input 
and outputs a collection of regions (or segments). 
For Single 
Objects
Classification
Classification + 
Localisation
For Multiple 
Objects
Object 
Detection
Instance 
Segementation
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
  
 
Basics of Images  
We all see a lot of images around us and use them daily either through our mobile phones or computer 
system. But do we ask some basic questions to ourselves while we use them on such a regular basis.  
 
Don’t know the answer yet? Don’t worry, in this section we will study about the basics of an image:  
Basics of Pixels 
The word “pixel” means a picture element. Every photograph, in digital form, is made up of pixels. 
They are the smallest unit of information that make up a picture. Usually round or square, they are 
typically arranged in a 2-dimensional grid. 
In the image below, one portion has been magnified many times over so that you can see its individual 
composition in pixels. As you can see, the pixels approximate the actual image. The more pixels you 
have, the more closely the image resembles the original.