Python is a popular programming language that is widely used in the field of computer vision and image processing. One of the most popular libraries for working with images in Python is OpenCV (Open Computer Vision). OpenCV is an open-source library that provides a wide range of tools for image and video processing, including face detection, object tracking, and image filtering.

We at Pranon, the goal of our company is to create products for blockchain and artificial intelligence. Pranon may decide to create an AI product utilizing OpenCV for a variety of reasons, including the following:

  • OpenCV is a widely used, open-source library for computer vision and image processing. It has a large community of developers and users, making it a reliable choice for developing AI
  • OpenCV offers a wide range of algorithms and tools that can be used to develop AI products such as object detection, face recognition, and image classification. These tools can be easily integrated into the AI product being developed by Pranon.
  • Using OpenCV can help Pranon reduce development time and costs as they do not have to develop their own algorithms and tools from scratch.
  • As for their future goal, it is possible that Pranon is looking to develop AI products that can be used in a variety of industries such as security, healthcare, and retail. They may also be looking to expand their AI product offerings to include other areas such as natural language processing and machine learning. Ultimately, their goal is likely to continue innovating and delivering high-quality AI products that meet the needs of their customers.

Looking to the future, OpenCV is likely to continue to be a popular and widely used library in the field of computer vision. With the increasing demand for image and video processing, facial recognition, and robotics, OpenCV is well-positioned to continue to be a leader in these areas. Additionally, as machine learning and artificial intelligence become more important, OpenCV is likely to play a central role in the development of these technologies.

In this blog, I will share my experience, I did some of the basic concepts and techniques of using Python and OpenCV for image processing tasks. I started by setting up the environment and installing the necessary libraries and dependencies.

Once my environment was set up, I dived into some basic image processing tasks such as reading and displaying images, cropping and resizing images, and converting between color spaces. I also looked at some more advanced techniques such as image thresholding, edge detection, and morphological operations. I created a flowchart to better understand how OpenCV operates. The diagram is:

Figure: Flowchart for a camera-based system designed with OpenCV

One of the key features of OpenCV is its support for machine learning algorithms. I explored how to use OpenCV’s built-in machine-learning algorithms for tasks such as object detection and classification.

Finally, I looked at some practical applications of image processing using Python and OpenCV, such as face detection and recognition, object tracking, and image restoration.

Overall, Python and OpenCV are effective programs for working with images and video and provide a wide range of features for image processing and computer vision jobs. You can use Python and OpenCV to construct your own image-processing programs and address practical issues with a little effort and innovative thinking. Pranon develops AI solutions because it enables them to make use of Python’s ubiquity and usability while employing the OpenCV library’s capabilities.

Written By
Tihasha Rafa
Junior Software Engineer
Pranon Global Limited