Open CV

1. Introduction “If you’ve ever worked with image processing, you know that thresholding is one of the simplest yet most powerful techniques for segmentation. But here’s the problem—real-world images don’t play nice.” Why Global Thresholding Fails I’ve personally faced this issue countless times. You apply a simple threshold, expecting crisp binarization, but instead, parts of … Read more

1. Introduction “Video is the closest thing we have to teleportation.” – Steve Jobs once said that about FaceTime, but in the world of AI and Data Science, video processing is what bridges raw visual data to intelligent automation. Why Video Processing Matters I’ve worked with video data in multiple real-world applications—whether it was training … Read more

1. Introduction “If your camera isn’t calibrated, your computer vision model is basically looking at the world through a funhouse mirror—except there’s nothing fun about distorted images in a production system.” I’ve worked with camera calibration in multiple projects, from stereo vision setups to real-world object tracking. And trust me, an uncalibrated camera can ruin … Read more

1. Introduction “If you can detect lines, you can understand structure.” That’s something I learned early when working with computer vision. Whether you’re building a self-driving car or automating document analysis, detecting lines is often the first step toward making sense of an image. So, what exactly is line detection? In simple terms, it’s identifying … Read more

I. Introduction “Text is everywhere—on street signs, product labels, scanned documents, you name it. But making a machine accurately detect and extract it? That’s a whole different challenge.” Over the years, I’ve worked with multiple text detection methods, from traditional computer vision techniques to deep learning-based approaches. Some work like magic on clean documents, while … Read more

I. Introduction “A good tool in the wrong hands is useless. A great tool in the right hands? Game-changing.” Object recognition is one of those things that seems deceptively simple—until you actually start implementing it. When I first started working with OpenCV for object recognition, I thought, How hard can it be? Just feed in … Read more

1. Introduction (Brief & Straight to the Point) “Theory is great, but if you can’t build something real with it, what’s the point?” I’ve worked on countless computer vision projects, and if there’s one thing I’ve learned, it’s this: practical implementation beats theoretical knowledge every single time. You can read all the papers you want, … Read more

1. Introduction “Your eyes say more than your words ever could.” – That’s not just a poetic thought; it’s a reality that technology is now learning to interpret. Eye tracking has fascinated me for years, especially with its applications in AR/VR, gaming, marketing, and even assistive technology. The idea that a system can analyze where … Read more

Criteria for Choosing a Computer Vision Library (Expert Perspective) Before we jump into the list of libraries, let’s talk about how you should evaluate them. Not all computer vision tools are built the same, and picking the wrong one can lead to wasted effort. Over the years, I’ve worked with everything from OpenCV to PyTorch … Read more

1. Introduction “The real voyage of discovery consists not in seeking new landscapes, but in having new eyes.” – Marcel Proust That quote perfectly sums up what OpenCV does for us in computer vision—it gives us new eyes, digital ones. I’ve worked with OpenCV across multiple languages—Python, C++, even MATLAB at some point. But when … Read more