In a nutshell: Short History of OpenCV

Today, I want to talk about the history of OpenCV, one of the coolest computer vision libraries out there. Since you have already decided to read this, I assume that you already heard about OpenCV. OpenCV has come a long way since its humble beginnings, and it's pretty awesome to see where it's at now. So let's start.

The Beginning: 1999

OpenCV was created by a team of researchers at Intel's research labs, led by Gary Bradsky. It was just a project at the beginning and they even didn't believe it would have such a big impact on the future. Here is what Bradski says:

"OpenCV started as a research project, but it quickly became clear that the potential applications were much wider than we initially thought. We wanted to make computer vision accessible to a wider audience, and OpenCV was the perfect platform to do that."

But what was the goal ? Let's learn it from Bradski also:

"The goal of OpenCV was always to democratize computer vision and make it more accessible to developers and researchers. We wanted to make it easy for people to use machine perception in their own projects and applications."

In summary, OpenCV was born in Intel's lab with a commercial project and it is converted into a famous computer vision library, it's all thanks to the vision of Gary Bradski and his team.

Growing Popularity: 2005-2010

By the mid-2000s, OpenCV had grown in popularity and was widely recognized as a valuable resource for computer vision research and development. It became one of the most widely used computer vision libraries in the world, with thousands of users and contributors. OpenCV also gained recognition from industry leaders, who saw its potential for practical applications in fields such as security, surveillance, and robotics.

In my opinion, the most important point which makes OpenCV such famous was that it was the first. So whoever needs a technology related to Computer Vision, would find OpenCV because there isn't a corresponding one. One of the other secrets of OpenCV’s popularity was its open-source nature. With the trigger of this, many developers and researchers had a chance to contribute and help to build OpenCV.

In 2007, OpenCV reached a major milestone when it was included in the Google Summer of Code program. This provided students with the opportunity to work on real-world computer vision projects and gave OpenCV exposure to a new generation of computer vision researchers and practitioners.

2010-Present

The most significant advancements during these years were in the field of deep learning and artificial intelligence. Inevitably, these advancements also affected the computer vision field. Thus, OpenCV was directly impacted as well. OpenCV was quite advantageous at this point. By the time it reached 2010, it had increased the number and diversity of its functions, and it had a large number of developers. Furthermore, its popularity was at its peak. So OpenCV easily adapted and expanded its functionalities to include new application areas, such as deep learning, augmented reality, and object detection.

In recent years, OpenCV has become an essential tool for computer vision researchers and practitioners around the world. It is widely used in industry, academia, and research, and has been adopted by a variety of organizations, from large tech companies to small startups. OpenCV has also been used in many exciting and innovative projects, from self-driving cars to medical imaging, and has been instrumental in advancing the field of computer vision.

Conclusion

OpenCV has come a long way since its inception in 1999 and has had a profound impact on the field of computer vision. Its open-source nature and focus on collaboration and sharing have made it a central resource for computer vision research and development. With its growing popularity and wide range of features and algorithms, OpenCV is sure to continue to play a key role in the future of computer vision.

By the way, I also create content on YouTube which are related to the OpenCV library. I am trying to get into the deep of all functions inside the library. You may check.