In this tutorial, let’s see how easy to find all contours in an image with OpenCV APIs.
Barcode is an efficient way to make information readable for machines. There are many scenarios of using Barcode reader software. For example, companies use Barcode encoding and decoding software to manage various documents that captured by office scanners. Airport security uses handheld scanners to check the boarding pass and record personal information to the database. Students use the built-in camera of the smartphone to check attendance via Barcode reader software. Since I have a Webcam connected to my desktop PC, I want to empower it to work as a Barcode reader. To implement the solution, I decide to choose OpenCV and Dynamsoft Barcode Reader SDK.
In this tutorial, let’s learn how to use Hough line transformation with OpenCV to make line detection in an Image.
Changes or discontinuities of amplitude attribute, such as luminance value, are fundamentally important primitive characteristics of an image. They often provide an indication of the physical extent of objects. Local Discontinuities of image luminance that from one level to another are called luminance edges. In this post, I’ll share how to make image edge detection with OpenCV.
OpenCV (Open Source Computer Vision Library) is a powerful open source library of computer vision algorithms. It is widely used by many technologies, such as image acquiring (e.g. Webcam capture), image processing (e.g. noise reduction), image detection (e.g. face detection), image recognition (e.g. OCR), and so on. Since all OpenCV source code is on GitHub, let’s get the copy and build the source code ourselves for fun.