Universal Barcode Detector via Semantic Segmentation

Barcodes are used in many commercial applications, thus fast and robust reading is important. There are many different types of barcodes, some of them look similar while others are completely different. In this paper we introduce new fast and robust deep learning detector based on semantic segmentation approach. It is capable of detecting barcodes of any type simultaneously both in the document scans and in the wild by means of a single model. The detector achieves state-of-the-art results on the ArTe-Lab 1D Medium Barcode Dataset with detection rate 0.995. Moreover, developed detector can deal with more complicated object shapes like very long but narrow or very small barcodes. The proposed approach can also identify types of detected barcodes and performs at real-time speed on CPU environment being much faster than previous state-of-the-art approaches

Improved QR code localization using boosted cascade of weak classifiers

Usage of computer-readable visual codes became common in our everyday life at industrial environments and private use. The reading process of visual codes consists of two tasks: localization and data decoding. Unsupervised localization is desirable at industrial setups and for visually impaired people. This paper examines localization efficiency of cascade classifiers using Haar-like features, Local Binary Patterns and Histograms of Oriented Gradients, trained for the finder patterns of QR codes and for the whole code region as well, and proposes improvements in post-processing

A review of the current trends and future directions of camera barcode reading

Modern mobile phones or smartphones have become a pervasive and affordable device for users at different levels of age around the world. Smartphones equipped with many useful sensors, including camera, barometer, accelerometer, and digital compass. The sensors on smartphones attracted researchers and developers to develop mobile applications (apps) and study the potential use of the sensors to support daily life activities. Unlike other types of sensor, the smartphone camera has been underutilized. Analysis of the literature suggested that smartphone camera mainly serves for personal and social photography. Practically, a smartphone camera can be used as an imaging device for reading a barcode. Although barcode has been used for identifying products and items, the use of a smartphone camera as a reading device has not been explored thoroughly. Further, scholarly resources describing the fundamental knowledge of smartphone camera barcode reading is not available in the literature which could be the reason contributed to slow research progress of the domain. Therefore, this study aims to review the current trends and future directions of smartphone camera for barcode reading. Specifically, the study reviews the literature on the types of applications that are currently available and run on the standard mobile platform for reading a barcode. It also analyzes the necessary components that made up barcode reading apps. Further, the review identifies technical and non-technical issues that are critical for the development of the apps. The contributions of this work are twofold, first, it provides the fundamental knowledge on the building blocks of camera barcode reading apps, and second, it explores the issues in the current camera barcode reading apps that could encourage exploration towards addressing the issues. Practically, the findings could spark new research ideas to address the current issues related to the use of smartphone camera for barcode reading in the near future

Blur-resistant joint 1D and 2D barcode localization for smartphones

With the proliferation of built-in cameras barcode scanning on smartphones has become widespread in both consumer and enterprise domains. To avoid making the user precisely align the barcode at a dedicated position and angle in the camera image, barcode localization algorithms are necessary that quickly scan the image for possible barcode locations and pass those to the actual barcode decoder. In this paper, we present a barcode localization approach that is orientation, scale, and symbology (1D and 2D) invariant and shows better blur invariance than existing approaches while it operates in real time on a smartphone. Previous approaches focused on selected aspects such as orientation invariance and speed for 1D codes or scale invariance for 2D codes. Our combined method relies on the structure matrix and the saturation from the HSV color system. The comparison with three other real-time barcode localization algorithms shows that our approach outperforms the state of the art with respect to symbology and blur invariance at the expense of a reduced speed

Automation and Robotics: Latest Achievements, Challenges and Prospects

This SI presents the latest achievements, challenges and prospects for drives, actuators, sensors, controls and robot navigation with reverse validation and applications in the field of industrial automation and robotics. Automation, supported by robotics, can effectively speed up and improve production. The industrialization of complex mechatronic components, especially robots, requires a large number of special processes already in the pre-production stage provided by modelling and simulation. This area of research from the very beginning includes drives, process technology, actuators, sensors, control systems and all connections in mechatronic systems. Automation and robotics form broad-spectrum areas of research, which are tightly interconnected. To reduce costs in the pre-production stage and to reduce production preparation time, it is necessary to solve complex tasks in the form of simulation with the use of standard software products and new technologies that allow, for example, machine vision and other imaging tools to examine new physical contexts, dependencies and connections