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

Distance transform and template matching based methods for localization of barcodes and QR codes

Visual codes play an important role in automatic identification, which became an inseparable part of industrial processes. Thanks to the revolution of smartphones and telecommunication, it also becomes more and more popular in everyday life, containing embedded web addresses or other small informative texts. While barcode reading is straightforward in images having optimal parameters (fo cus, illumination, code orientation, and position), localization of code regions is still challenging in many scenarios. Every setup has its own characteristics, there fore many approaches are justifiable. Industrial applications are likely to have more fixed parameters like illumination, camera type and code size, and processing speed and accuracy are the most important requirements. In everyday use, like with smart phone cameras, a wide variety of code types, sizes, noise levels and blurring can be observed, but the processing speed is often not crucial, and the image acquisition process can be repeated in order for successful detection. In this paper, we address this problem with two novel methods for localization of 1D barcodes based on template matching and distance transformation, and a third method for QR codes. Our proposed approaches can simultaneously localize sev eral different types of codes. We compare the effectiveness of the proposed methods with several approaches from the literature using public databases and a large set of synthetic images as a benchmark. The evaluation shows that the proposed methods are efficient, having 84.3% Jaccard accuracy, superior to other approaches. One of the presented approaches is an improvement on our previous work. Our template matching based method is computationally more complex, however, it can be adapted to specific code types producing high accuracy. The other method uses distance transformation, which is fast and gives rough regions of interests that can contain valid visual code candidates

QR Code Approach for Examination Process

Using the QR codes is one of the most intriguing ways of digitally connecting consumers to the internet via mobile phones since the mobile phones have become a basic necessity thing of everyone The detection of QR codes, a type of 2D barcode, as described in the literature consists merely in the determination of the boundaries of the symbol region in images obtained with the specific intent of highlighting the symbol .In order to improve the practical application property of the two-dimensional barcode Quick Response (QR) code, we investigate the coding and decoding process of the QR code image. The barcode is a real mechanism for data reads. Data can be stored, embedded and through the scanning device to show. The store of data which being read. In this paper, we present a methodology for creating QR code approach for virtual word examination process by using different techniques like SHA256, encoding, decoding, and Error correction. DOI: 10.17762/ijritcc2321-8169.15024

Rapid detection of multi-QR codes based on multistage stepwise discrimination and a compressed mobilenet.

Poor real-time performance in multi-QR codes detection has been a bottleneck in QR code decoding based Internet-of-Things (IoT) systems. To tackle this issue, we propose in this paper a rapid detection approach, which consists of Multistage Stepwise Discrimination (MSD) and a Compressed MobileNet. Inspired by the object category determination analysis, the preprocessed QR codes are extracted accurately on a small scale using the MSD. Guided by the small scale of the image and the end-to-end detection model, we obtain a lightweight Compressed MobileNet in a deep weight compression manner to realize rapid inference of multi-QR codes. The Average Detection Precision (ADP), Multiple Box Rate (MBR) and running time are used for quantitative evaluation of the efficacy and efficiency. Compared with a few state-of-the-art methods, our approach has higher detection performance in rapid and accurate extraction of all the QR codes. The approach is conducive to embedded implementation in edge devices along with a bit of overhead computation to further benefit a wide range of real-time IoT applications

FlightGoggles: A Modular Framework for Photorealistic Camera, Exteroceptive Sensor, and Dynamics Simulation

FlightGoggles is a photorealistic sensor simulator for perception-driven robotic vehicles. The key contributions of FlightGoggles are twofold. First, FlightGoggles provides photorealistic exteroceptive sensor simulation using graphics assets generated with photogrammetry. Second, it provides the ability to combine (i) synthetic exteroceptive measurements generated in silico in real time and (ii) vehicle dynamics and proprioceptive measurements generated in motio by vehicle(s) in a motion-capture facility. FlightGoggles is capable of simulating a virtual-reality environment around autonomous vehicle(s). While a vehicle is in flight in the FlightGoggles virtual reality environment, exteroceptive sensors are rendered synthetically in real time while all complex extrinsic dynamics are generated organically through the natural interactions of the vehicle. The FlightGoggles framework allows for researchers to accelerate development by circumventing the need to estimate complex and hard-to-model interactions such as aerodynamics, motor mechanics, battery electrochemistry, and behavior of other agents. The ability to perform vehicle-in-the-loop experiments with photorealistic exteroceptive sensor simulation facilitates novel research directions involving, e.g., fast and agile autonomous flight in obstacle-rich environments, safe human interaction, and flexible sensor selection. FlightGoggles has been utilized as the main test for selecting nine teams that will advance in the AlphaPilot autonomous drone racing challenge. We survey approaches and results from the top AlphaPilot teams, which may be of independent interest.Comment: Initial version appeared at IROS 2019. Supplementary material can be found at https://flightgoggles.mit.edu. Revision includes description of new FlightGoggles features, such as a photogrammetric model of the MIT Stata Center, new rendering settings, and a Python AP

QR code detection under ROS implemented on the GPU

Tato diplomová práce se zabývá vývojem a implementací algoritmu pro detekci QR kódů s integrací do platformy ROS a výpočty běžícími na grafické kartě. Z rešerše současně dostupných nástrojů a technik je vybrán vhodný postup a algoritmus je napsán jako modul v programovacím jazyce Python, který je snadno integrovatelný do ROS. Ke zprostředkování výpočtů na vícejádrovém hardware, jako jsou grafické karty či vícejádrové procesory, je využita knihovna OpenCL.This master's thesis deals with the design and implementation of a QR code detection algorithm under the ROS platform with computations running on a graphical processing unit. Through a comparative survey of available tools and techniques, a suitable approach is chosen and the algorithm is written as a module in the Python programming language, ready to be implemented under the ROS platform. The OpenCL parallel computing platform is used to facilitate parallel computation on multi-core hardware, such as graphical processing units or multi-core CPUs.

Automatikus azonosítás és hitelesítés vizuális kódokkal

Az automatikus azonosítás egyik legfontosabb és széles körben alkalmazott eleme a vizuális kódokkal történő azonosítás. A különbözô szimbólumokkal és mintákkal megjelenített azonosítók teszik lehetôvé a gépek számára az elektronikus leolvasást, ami nagyban segíti és gyorsítja a feldolgozást pl. a bolti pénztáraknál, raktári átvételnél, nagy sebességű feldolgozási helyeken, gyártósorokon. A szokásosan használt, geometriai minták szerint tervezett kódok általában típusokat vagy egyedeket azonosítanak. Elôállíthatók azonban olyan mintázatok, melyek természetüknél fogva egyediek és így eredetiség vagy hitelesség ellenôrzésére is alkalmazhatók. Jelen írásunkban bemutatunk egy módszert QR kódok gyors és pontos detektálására mobil készülékkel készített fényképeken, valamint egy természetes mintázat felismerésére kidolgozott eljárásunkat. Alkalmazási területként bemutatunk egy olyan lehetséges hibrid vizuális kód konstrukciót, melyben mesterséges és természetes mintázatok együttes alkalmazásával elérhetô az azonosítás és a hitelesítés is

Penerapan Location Based Service (LBS) dan QR Code Detection pada Aplikasi Pemetaan dan Penjemputan Retribusi Parkir Kendaraan Berbasis Android

One source of regional income for Cilacap Regency is the management of vehicle parking lots. Currently, parking area management is carried out by recording the identity of the parking location based on the street name, while the withdrawal of parking fees is carried out by towing officers who come to the parking location and then record it in a book. The current management of parking lots is still inaccurate because there are several street names that have more than one parking area which results in data redundancy. The conventional parking fee collection system causes frequent discrepancies in reports due to the potential for misuse of parking fees. The absence of tools that can be used by related agencies to control reports is the cause of the problem. The research objective is to develop an information system by applying LBS technology which functions to detect parking points precisely and QR Code Detection which functions to detect the identity of parking attendants. System development uses the ADDIE model. The results of the research are an information system for mapping parking lots and picking up parking fees based on Andorid which can help manage vehicle parking lots which includes mapping the location of parking lots and picking up vehicle parking fees