This article is about how to use OpenCV and Dynamsoft Barcode Reader SDK to create a Python barcode reader on macOS.
Previously, I wrote an article Raspberry Pi Barcode Scanner with Webcam and Python illustrating how to build a simple barcode scanner using Dynamsoft Barcode Reader SDK and OpenCV from scratch. The method decodeFile() was used for detecting barcodes from an image file. To use the API, you have to firstly write image buffer that obtained by OpenCV API to a file. Because the I/O operation takes too much time, this API is not suitable for real-time barcode detection from webcam video stream. Considering this scenario, I have added a new Python API decodeBuffer(). In this article, I will illustrate how to create and use the new API.
OpenCV officially provides both C++ and Python APIs for developers. Most of the time, developers just need to use one kind of programming languages to read, write and process images with hundreds of computer vision algorithms. However, if you want to use OpenCV Python APIs with an extended C/C++ library, it will be tricky to pass the data. In this article, I will share how to read camera stream with OpenCV-Python and detect barcode with Dynamsoft C/C++ Barcode SDK.
Dynamsoft Barcode Reader C++ SDK is available for Windows, Linux, and Mac (iOS and Android editions are coming soon). I have shared an article that illustrates how to build webcam barcode reader in Python. In this tutorial, I’ll use a different C++ API to implement barcode scanner applications for Windows and Raspberry Pi with a webcam.
In reality, we can always see some photos that have low brightnesses and low contrast. To make objects recognizable in pictures, we need to process the photo with Illumination Compensation. There are many algorithms used for Illumination Compensation such as Histogram equalization, Color similarity measure, Gamma Correction and so on. In this tutorial, I will introduce Gamma Correction and show you how to use it with OpenCV.
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.