Latest computer vision mini projects

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Latest computer vision mini projects

Summary: Computer vision is one of the latest technologies that is going to have a great impact on AI powered Robotics, which is literally our future. You need to get skilled on computer vision as early as possible to put yourself ahead of your peers. And developing projects on them is a great way to develop the skills. Building projects can be very challenging on computer vision, but it is not very difficult due to the recent technological advancements and resources available.

Here are some of the latest mini projects you can do on computer vision:

  1. Computer Vision based Mouse
  2. Computer Vision based Text Scanner
  3. Computer Vision based Smart Selfie
  4. Surveillance Robot
  5. Sixth Sense Robot
Read more..

Late in 1966, Prof. Seymour Papert at MIT asked his graduate students to ‘plug a camera into a computer and describe what it sees’ as a summer project. Those graduate students surely had a tough time, since their project wasn’t completed due to technical discrepancies - but this idea is what computer vision is.

Ideally Computer vision is described as “an interdisciplinary scientific field that deals with how computers can be made to gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do”. To make it simple, Computer vision is the study of algorithmic methods for analyzing and interpreting visual image data.

Let's say, I have built a robot (a computing machine) and I want it to recognize different colors such as green, yellow, white, etc., the same way a human being does. We as human beings can achieve this because we have higher intelligence (or higher cognitive processing capacity) but how can we make a robot achieve the same? So, at that moment we use our knowledge and understanding of graphics and embed that knowledge onto the robot/ computer by means of programs/codes to make them recognize and distinguish different colors. Although this is a simple example, the complexity of this field is much higher than this. But, you get the general idea.

Great Projects with Kits and Video Tutorials for Engineering Students

In addition to the many fields it intersects, computer vision is complicated by the highly varying agendas of its practitioners. People working on the same problem, such as face recognition, may have very different approaches, not because they disagree on fundamental principles, but more because they have different goals. In this article, we will examine computer vision from a variety of perspectives as defined by goals of different researchers.

Computer Vision & Engineering:

A good deal of the field research is focused on developing applications that can be used in the real world. Some examples include quality control in manufacturing, optical character recognition, driver assistance systems, surveillance, photography and entertainment.

At the risk of oversimplifying the discussion, we will refer to this as the “Engineering” approach to computer vision. The goal in this approach is to make things work. This work in general is characterized by

  • Solving real-world problems in need of a solution, rather than “toy” problems
  • Making vision methods fast enough to be useful, or faster so that they are more useful
  • Making vision systems more robust, so that they work in a wider range of environments and applications
  • Designing systems using currently available technology, so that it is easier to predict the successful completion of specific projects

Sometimes the engineering approach carefully specifies a narrow application domain, and builds a highly specialized application which would fail in any other domain, but works very well in the specified domain. For example, techniques for analyzing printed circuit boards for flaws rely on careful alignment of the target board with respect to a video camera, a fixed lighting arrangement, and assumptions about the type of camera used. Such product inspection systems represent one highly successful area of computer vision based algorithms. However, few people would expect such algorithms to be useful to an autonomous robot for recognizing faces. They simply weren’t designed for the same thing. So, they don’t function efficiently.

There are many practical vision problems that we are not yet able to solve.

For example, there would be many applications of a program that could look at a photograph and name the people in it. While we have made some progress on this problem, we are not nearly as good at it.

Given that there are certain problems for which we cannot yet engineer a sufficiently high quality solution, the question emerges about how to best proceed towards a solution. One method is to focus on engineering systems that are as good as possible, and try to make incremental progress on an easily quantifiable measure of fitness, such as accuracy on a face recognition task.

A completely different approach is to study the central principles of computer vision and natural vision systems and then build fundamentally new systems using this new understanding. The danger, of course, is that we never return from these fundamental investigations of core principles to build a useful vision system. Nevertheless, there are a large number of vision researchers who are focused on understanding the principles behind vision rather than producing short-term artifacts.

To understand the scope of Computer vision even further, Mark 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."

Needless to say this is the future of Image processing and Data Science.

Now you know how important it is to build applications based on computer vision. And this is not a simple task as it looks. So, building projects can be very challenging on computer vision, but it is not very difficult due to the recent technological advancements and resources available.

So, you can now be rest assured that you will get all the resources needed to get started on your computer vision. And what better way to showcase your skills than by building computer vision projects for your academic mini projects.

Just imagine, how cool you will look in front your recruiters when you present a mini project profile on computer vision!

Ready to be the innovator that the world needs today?

In this article we are also mentioning about some of the best computer vision mini project topics which you can do.

Now let us have a look at the interesting project ideas that can help you specialize and develop a sound profile in Computer Vision -

Build Computer Vision Based Text Scanner

The goal of Text Recognition application is to recognize the text from a printed hardcopy document to display it on a digital screen. The process of Text Recognition involves several steps including preprocessing, segmentation, feature extraction, classification, post processing. Preprocessing is done as the basic operation on input image like binarization which convert gray scale image into Binary Image and noise reduction algorithm is used to remove the noisy signal from image. Segmentation stage is to segment the given image into line by line and segment each character from segmented line. Feature extraction calculates the characteristics of character. A classification contains the database and does the comparison. Nowadays it plays an important role in office, colleges etc.

You can now develop this project right from home by getting expert guidance from Skyfi Labs.

Check the project details

Build Computer Vision Based Mouse

With this project you can control and command the cursor of a computer or a computerized system using a camera. In order to move the cursor on the computer screen the user simply have to move a colored object on a surface within the viewing area of the camera. The video generated by the camera is analyzed using computer vision techniques and the computer moves the cursor according to the colored object movements. The computer vision based mouse has corresponding region where you can show dedicated colored objects for clicking action.

Sounds pretty cool right?

Now you can develop this project right from your home itself and impress your recruiters/ project coordinators. You will also get good expert guidance from Skyfi Labs to make this project work seamlessly.

Check the project details here

Build Surveillance Robotics Project

This project proposes an architecture for an intelligent surveillance system, where the aim is to mitigate the burden on humans in conventional surveillance systems by incorporating intelligent interfaces, computer vision, and autonomous mobile robots.

With this project, you can control a robot and view live footages from any remote location and navigate to places that are harmful for human beings. These robots are very much useful for detecting bombs, search & rescue operations etc.

Moreover, these scenarios demonstrate how technology enables robots to effectively balance surveillance objectives, autonomously performing the job of human patrols and responders.

And we at Skyfi Labs have developed an innovative methodology to make it very easy for you to learn and build this project. You can get the components needed to build this project right to your home and build using online tutorials.

Get the Surveillance Robots kit to your home

Build Computer Vision Based Smart Selfie Application

Computational photography is a digital image processing technique that uses algorithms to replace optical processes, and it seeks to improve image quality by using machine vision. It is about taking studio effects that you achieve with Lightroom and Photoshop and making them accessible to people at the click of a button.

These days many research oriented startups provide much of the computational technology to camera brands. With advanced image processing technology enabled by Computer Vision you're able to smooth the skin and get rid of blemishes, but not just by blurring it – you also get texture. In the past, the technology behind ‘smooth skin’ and ‘beauty’ modes has essentially been about blurring the image to hide imperfections.

Now it’s about creating looks that are believable, and AI plays a key role in that. For example, AI is used to train algorithms about the features of people's face.

With this application, you can also program it to automatically take a snap when you smile and look your very best.

Sounds very appealing?

You can now develop this application right from your home. Complete course content and guidance will be provided by Skyfi Labs to help you build this project with 100% output. Why wait, start building now.

Try a free demo of smart selfie project

Hope you got some good computer vision based mini project ideas from this article.

Suppose, if you want to build great computer vision based mini 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.

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

Good luck for your computer vision mini project!




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