Assume you apply barcode technology to the logistics conveyor belt for scanning parcels. A problem you may face is how to recognize barcodes from blurred images. Although we can use advanced algorithms to deal with this complicated case, we’d better improve the image quality as possible as we can. A simple way is to adjust the camera shutter speed which is also known as exposure time. Faster shutter speed can avoid motion blur. In this post, I will share how to invoke Android Camera2 APIs to change the shutter speed, as well as how to build a simple Android barcode reader to decode barcodes from fast-moving objects
If you want to use Raspberry Pi as an economical way of detecting barcodes, you can take account for Dynamsoft Barcode Reader SDK. As a business software, Dynamsoft Barcode Reader SDK is designed for overcoming a variety of complicated scenarios with sophisticated algorithms and heavy computations. Although the SDK is flexible for customizing algorithm parameters, subject to the low-frequency CPU of Raspberry Pi, the tradeoff between recognition accuracy and detection speed is still a big challenge. In this article, I will use Socket client-server model as a substitute solution. Thanks to Sabjorn’s NumpySocket module.
Qt for Python enables developers to quickly create GUI apps on Windows, Linux and macOS with one codebase. In this article, I will share how to build a Python barcode reader with Qt on Windows. Since Dynamsoft Barcode Reader SDK is also cross-platform, it is easy for you to reuse the sample code on Linux and macOS.