Computer Vision

Best Final Year Computer Vision (CV) Projects (Videos Included)

Summary: If you are interested in developing an exciting career on computer vision, you should start developing hands-on skills on them. Since it is new technology, our colleges don’t have the necessary infrastructure or the expertise to guide people in learning them. A good way to gain skills on them is to start building projects.


Note about Computer Vision Note:

Have you checked out our projects on Computer Vision yet?
Computer Vision Kit will be shipped to you and you can build using tutorials. You can start with a free demo today!

1. Surveillance Robot

2. Sixth Sense Robot

3. 3 Computer Vision Projects (Combo Course)

4. Computer Vision - Text Scanner

5. Computer Vision Based Mouse

6. Computer Vision Based Smart Selfie

7. Computer Vision Training & Internship


Read more..

Computer vision is a field of computer science which enables a computer to see, identify and process the images in a way we humans do. And analyzes the information gathered from the image to produce a desired output. This is basically a process of imparting human intelligence and instincts to a computer.

Computer vision is very much linked with image processing and artificial intelligence. Computer vision can also be stated as the automatic extraction, analysis and understanding of useful information from a single image or a sequence of images. Humans use their eyes and their brains to see and visually sense the world around them. Computer vision is the science that aims to give a similar, if not better, capability to a machine or a computer.

For this process to successfully take place, the computer must interpret what it sees, and then perform appropriate analysis or act accordingly.

Computer vision not only aims at seeing, but also processes and provides useful results based on the observation. For example, a computer can create a 3D image from a 2D image, in a way those in cars and provide important data to the driver. Cars today could be fitted with these technologies and help them to identify and distinguish objects on the road like traffic lights, pedestrians, traffic signs etc. and henceforth act accordingly.

If we talk about the Scope of computer vision in the future, we can look at the various application of this technology in today’s time.

  • Agriculture
  • Augmented reality
  • Autonomous vehicles
  • Biometrics
  • Character recognition
  • Forensics
  • Industrial quality inspection
  • Face recognition
  • Gesture analysis
  • Geoscience
  • Image restoration
  • Medical image analysis
  • Pollution monitoring
  • Process control
  • Remote sensing
  • Robotics
  • Security and surveillance
  • Transport

Zuckerberg said, “If we could build computers that could understand what's in an image and could tell a blind person who otherwise couldn't see that image, that would be pretty amazing as well," "This is all within our reach and I hope we can deliver it in the next 10 years."

And trust me, we are not very far from this to happen. We are already experiencing the impact that computer vision has created today. From the face unlock feature that we have in our mobile to the latest shopping innovation “Amazon GO”, uses computer vision to provide a better experience to us.

After knowing what computer vision means, let us see how it actually benefits us. Computer vision provides direct benefits to the users by cutting down the time required for developing and creating an end product which the actual user wants. This is a boon for new developers who rely on Artificial Intelligence and Machine Learning to identify major patterns. Using computer vision, now they can finally end up having a more tailored, user friendly product.

Computer vision is the future and is surely a massive step towards creating an invisible technology which adopts the user’s need instantly and predicts their future needs with uncanny accuracy.


Latest projects on Computer Vision

Want to develop practical skills on Computer Vision? Checkout our latest projects and start learning for free


How to develop skills in computer vision?

To develop skills related to computer vision let us see what responsibilities that an engineer in this field will have,

  • Design, train and improve the algorithms that power our emotions analysis and crowd analytics platforms
  • Work on high performance computer vision products in real world use cases
  • Work with the development teams to productize the results of your research and development

Computer vision is so much linked with human vision and actions that one has to clearly notice what our eye can do and how it processes every action. After that, we need to analyze how our brain captures all these images and responds to this.

Once this whole process is clear, we can implicate this behavior onto the computer’s database and make it act accordingly. For example, in case of any accident, our brain stimulates stigmas so that we automatically pull the brake in order to save ourselves. This being the Psychological fact, let us see what all technical knowledge you need to get skilled in this field.

The typical core subjects for computer vision are:

  • Linear Algebra
  • Digital image processing
  • Programming: Matlab, Python, C/C++
  • Calculus 1 & 2
  • Statistics
  • Machine Learning
  • AI
  • Signal processing

When you know that you have the skills, then you can start building interest in computer vision by trying out smaller projects. Enrolling to online courses which focuses on computer vision and machine learning is one efficient way to learn. You can also attend certain workshops to get a more practical idea as to how projects are built on computer vision. And finally, you can create your own projects based on your creativity.

Build computer vision projects from home

5 key considerations while building projects on computer vision:

  1. Image classification: Given a set of images that are all labeled with a single category, one should know how to predict these categories for a novel set of test images and measure the accuracy of the predictions. 
  2. Object detection: One should be able to detect an object within an image accurately
  3. Object tracking: This basically means tracking a specific object of interest or multiple objects in a particular scene of a video
  4. Semantic Segmentation: Central to Computer Vision is the process of Segmentation, which divides whole images into pixel groupings which can then be labelled and classified
  5. Instance Segmentation: It segments different instances of classes, such as labelling 5 cars with 5 different colors. In classification, there’s generally an image with a single object as the focus and the task is to say what that image is. But in order to segment instances, we need to carry out far more complex tasks. We see complicated sights with multiple overlapping objects and different backgrounds, and we not only classify these different objects but also identify their boundaries, differences, and relations to one another.

How to build Computer Vision projects Did you know

Skyfi Labs helps students develop skills in a hands-on manner through Computer Vision Online Courses where you learn by building real-world projects.

You can enrol with friends and receive kits at your doorstep.

You can learn from experts, build working projects, showcase skills to the world and grab the best jobs.
Start Learning Computer Vision today!


Hope now you understood the importance of learning computer vision and what future does it hold for emerging engineers. If you are interested in developing an exciting career on computer vision, you should start developing hands-on skills on them. Since it is new technology, our colleges don’t have the necessary infrastructure or the expertise to guide people in learning them.

And what better way to learn computer vision than by building projects. So start learning today by building projects on computer vision hands-on.

Below are some interesting computer vision based final year projects that you can build to get skilled.

Latest computer vision final year projects for engineering students

Build Computer Vision Based Text Scanner

This project focusses on developing an application through which a computer can scan any text from an image using the optical character recognition algorithm and display the text on the screen.

Key learnings:

  1. Image processing algorithms
  2. Image thresholding
  3. Image perspective transformation
  4. Optical character recognition

Learn more about this project

Build Computer Vision Based Mouse

With this project you can develop a virtual mouse to control the cursor using the object tracking algorithm. Using this project, you can carry out all the functionalities of a mouse by just showing corresponding colors in the webcam. 

Key learnings:

  1. Image processing algorithms
  2. Image thresholding
  3. Canny edge detection
  4. Object tracking

Learn more about this project

Build Surveillance Robotics Project

In this course, you will learn to build your very own surveillance robot that uses Raspberry Pi as a microcontroller and transmits live video footage over the internet. You will also program the robot to get instructions from a user at a remote location.

Key learnings:

  1. Robot’s locomotion
  2. Working of DC motors & motor driver circuit
  3. Application of OpenCv
  4. Raspberry Pi architecture and its programming

Learn more about this project

Build Computer Vision Based Smart Selfie Application

In this project you will learn to develop a computer vison based smart selfie that can take snaps automatically when you smile using facial feature recognition algorithm and store it on your device.

Key learnings:

  1. Image processing algorithms
  2. Face recognition
  3. Facial feature recognition
  4. Dlib C++ library

Learn more about this project

Rubik’s cube detection:

This project can help one in detecting if the Rubik’s cube is solved correctly or not. This will basically judge all the small cubes of the cube and analyze if every color on one side of the cube matches with each and finally if the cube is solved properly. D localization and orientation would be the main feature of this project.

Key learnings:

  1. Edge detection
  2. Color detection
  3. Feature extraction
  4. Java and Open CV

Car recognition in an image:

This project could be specially designed for security purposes wherein it can detect a particular car from the images fed in. For example, if police or any security agency is searching for a car that is linked with a crime and they can make use of this application to detect it from a footage.

Key learnings:

  1. Edge detection
  2. Object recognition
  3. 3D perspective geometry

Detection of cancer:

“Melanoma” is a component in our skin which induces cancer. In the last decade, skin cancer increased its incidence becoming a public health problem. Through this project we can detect this component in the very early stages so that the disease could be detected and treated properly. By detecting the asymmetry, border, color and diameter we can detect melanoma. This project is very useful in the healthcare sector and can save a lot of lives.

Key learnings:

  1. Shape detection
  2. Colour detection
  3. Image measurement
  4. Programming

Head pose estimation:

In many situations, one needs to know how the head is tilted with respect to a camera. In a driver assistance system, a camera looking at the driver’s face in a vehicle can use head pose estimation to see if the driver is paying attention to the road or not. This project would help in doing all these tasks. This can also be used in implementing various hands free games.

Key learnings:

  1. 2D-3D transformations
  2. Dlib C++ library
  3. Open CV

Computer-Vision Based Augmentation of a Whiteboard:

This project is going to be for all those creative people who want to conduct a meeting in a more interesting manner. The whiteboard on which all the dry-erase pens work is now augmented with the help of computer vision for scanning and spatially organizing texts and drawings on the surface.

Key learnings:

  1. Image detection
  2. Movement detection
  3. OpenCV

Visual awareness and long term autonomy for robotic assistants:

A major challenge in deploying robots into the real world is the design of an architectural framework which can provide long-term, natural and effective interactions with people. With this framework, key issues related to the robots' like ability to engage in interactions in a natural way, to deal with multiple users, and to be constantly aware of their surroundings, can be solved efficiently.

Hope you got some good computer vision final year project ideas from this article.

Suppose, if you want to build great final year projects on computer vision projects but don’t have the necessary technical knowledge, don’t worry!

We at Skyfi Labs have developed an innovative learning methodology through which you can learn the latest technologies by building projects hands-on right from your home. With the online course content available 24x7 and 1-1 technical assistance provided, developing great expertise on the latest technologies like computer vision will never be tough for you.

Check all Skyfi Labs Computer Vision Projects

Comment your queries below, we will assist you at the earliest.

Good luck for your computer vision final year project!

Best Final Year Computer Vision (CV) Projects (Videos Included)
Skyfi Labs Last Updated: 2022-05-18





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