A New Perspective on First Read Rate of 2D Barcodes in Mobile Applications

The first read rate (FRR) has been one of the traditional benchmark metric for measuring the performance of barcode systems. In recent studies, it has been noted that the FRR alone is not a complete measure of user experience, especially of barcodes in mobile applications. In this paper, we present a further three factors that would influence the user experience of mobile 2D barcodes. Our investigation is based on a quantitative survey of a controlled study participated by 250 lay users of mobile phones, through reading QRCode and Data Matrix barcodes with a variety of camera mobile phones. Observations from our study correlate well with findings from other works

Etäisyyden huomioiva kaksiulotteinen viivakoodi mobiilikäyttötapauksiin

Global internet use is becoming increasingly mobile, and mobile data usage is growing exponentially. This puts increasing stress on the radio frequency spectrum that cellular and Wi-Fi networks use. As a consequence, research has also been conducted to develop wireless technologies for other parts of the electromagnetic spectrum – namely, visible light. One approach of using the visible light channel for wireless communication leverages barcodes. In this thesis, we propose a 2D barcode that can display different information based on the distance between the barcode and the scanner. Earlier research on distance-sensitive barcodes has focused on providing a closer viewer more information as a closer viewer can see more detail. In contrast, we target use cases where a clear physical separation between users of different roles can be made, such as presentation systems. We evaluate two methods of achieving distance-awareness: color-shifting of individual colors, where a color changes tone at longer distances, and color blending, where two colors blend into a third color at longer viewing distances. Our results show that a modern smartphone is capable of leveraging color-shifting in ideal conditions, but external changes such as ambient lighting render color-shifting unusable in practical scenarios. On the other hand, color blending is robust in varying indoor conditions and can be used to construct a reliable distance-aware barcode. Accordingly, we employ color blending to design a distance-aware barcode. We implement our solution in an off-the-shelf Android smartphone. Experimental results show that our scheme achieves a clear separation between close and far viewers. As a representative use case, we also implement a presentation system where a single barcode provides the presenter access to presentation tools and the audience access to auxiliary presentation material.Maailmanlaajuinen internetin käyttö muuttuu yhä liikkuvammaksi, ja mobiilidatan käyttö kasvaa eksponentiaalisesti. Tämä kohdistaa yhä suurempia vaatimuksia radiotaajuusspektriin, jota mobiili- ja Wi-Fi-verkot käyttävät. Näin ollen tutkijat ovat kehittäneet langattomia teknologioita hyödyntäen myös muita sähkömagneettisen spektrin osia – erityisesti näkyvää valoa. Yksi näkyvän valon sovellus langattomassa viestinnässä ovat viivakoodit. Tässä työssä kehitämme kaksiulotteisen viivakoodin, joka pystyy välittämään eri tietoa katselijoille eri etäisyyksillä. Aiempi etäisyyden huomioivien viivakoodien tutkimus on keskittynyt tarjoamaan lähellä olevalle katselijalle enemmän tietoa, koska läheinen katselija näkee viivakoodin tarkemmin. Sitä vastoin me keskitymme käyttötapauksiin, joissa eri käyttäjäroolien välillä on selkeä etäisyydellinen ero, kuten esimerkiksi esitelmissä puhujan ja yleisön välillä. Tarkastelemme kahta menetelmää: yksittäisten värien muutoksia etäisyyden muuttuessa ja kahden värin sekoittumista etäisyyden kasvaessa. Tulostemme perusteella nykyaikainen älypuhelin pystyy hyödyntämään yksittäisten värien muutoksia ihanteellisissa olosuhteissa, mutta ulkoiset tekijät, kuten ympäristön valaistus, aiheuttavat liian suuria värimuutoksia käytännön käyttötapauksissa. Toisaalta värien sekoittuminen on johdonmukaista muuttuvassa sisäympäristössä ja sitä voidaan käyttää luotettavan viivakoodin luomisessa. Näin ollen me suunnittelemme etäisyyden huomioivan viivakoodin hyödyntäen värien sekoittumista. Toteutamme ratkaisumme yleisesti saatavilla olevalle Android-älypuhelimelle. Kokeellisten tulostemme perusteella menetelmämme saavuttaa selkeän erottelun läheisten ja kaukaisten katselijoiden välillä. Esimerkkikäyttötapauksena toteutamme myös esitelmäjärjestelmän, jossa sama viivakoodi antaa lähellä olevalle puhujalle nopean pääsyn esitystyökaluihin ja kauempana olevalle yleisölle pääsyn esityksen apumateriaaliin

Vision Based Extraction of Nutrition Information from Skewed Nutrition Labels

An important component of a healthy diet is the comprehension and retention of nutritional information and understanding of how different food items and nutritional constituents affect our bodies. In the U.S. and many other countries, nutritional information is primarily conveyed to consumers through nutrition labels (NLs) which can be found in all packaged food products. However, sometimes it becomes really challenging to utilize all this information available in these NLs even for consumers who are health conscious as they might not be familiar with nutritional terms or find it difficult to integrate nutritional data collection into their daily activities due to lack of time, motivation, or training. So it is essential to automate this data collection and interpretation process by integrating Computer Vision based algorithms to extract nutritional information from NLs because it improves the user’s ability to engage in continuous nutritional data collection and analysis. To make nutritional data collection more manageable and enjoyable for the users, we present a Proactive NUTrition Management System (PNUTS). PNUTS seeks to shift current research and clinical practices in nutrition management toward persuasion, automated nutritional information processing, and context-sensitive nutrition decision support. PNUTS consists of two modules, firstly a barcode scanning module which runs on smart phones and is capable of vision-based localization of One Dimensional (1D) Universal Product Code (UPC) and International Article Number (EAN) barcodes with relaxed pitch, roll, and yaw camera alignment constraints. The algorithm localizes barcodes in images by computing Dominant Orientations of Gradients (DOGs) of image segments and grouping smaller segments with similar DOGs into larger connected components. Connected components that pass given morphological criteria are marked as potential barcodes. The algorithm is implemented in a distributed, cloud-based system. The system’s front end is a smartphone application that runs on Android smartphones with Android 4.2 or higher. The system’s back end is deployed on a five node Linux cluster where images are processed. The algorithm was evaluated on a corpus of 7,545 images extracted from 506 videos of bags, bottles, boxes, and cans in a supermarket. The DOG algorithm was coupled to our in-place scanner for 1D UPC and EAN barcodes. The scanner receives from the DOG algorithm the rectangular planar dimensions of a connected component and the component’s dominant gradient orientation angle referred to as the skew angle. The scanner draws several scan lines at that skew angle within the component to recognize the barcode in place without any rotations. The scanner coupled to the localizer was tested on the same corpus of 7,545 images. Laboratory experiments indicate that the system can localize and scan barcodes of any orientation in the yaw plane, of up to 73.28 degrees in the pitch plane, and of up to 55.5 degrees in the roll plane. The videos have been made public for all interested research communities to replicate our findings or to use them in their own research. The front end Android application is available for free download at Google Play under the title of NutriGlass. This module is also coupled to a comprehensive NL database from which nutritional information can be retrieved on demand. Currently our NL database consists of more than 230,000 products. The second module of PNUTS is an algorithm whose objective is to determine the text skew angle of an NL image without constraining the angle’s magnitude. The horizontal, vertical, and diagonal matrices of the (Two Dimensional) 2D Haar Wavelet Transform are used to identify 2D points with significant intensity changes. The set of points is bounded with a minimum area rectangle whose rotation angle is the text’s skew. The algorithm’s performance is compared with the performance of five text skew detection algorithms on 1001 U.S. nutrition label images and 2200 single- and multi-column document images in multiple languages. To ensure the reproducibility of the reported results, the source code of the algorithm and the image data have been made publicly available. If the skew angle is estimated correctly, optical character recognition (OCR) techniques can be used to extract nutrition information

A comparison of barcoding and RFID technologies in practice

This research paper highlights inconsistencies in the way Radio Frequency Identification (RFID) is compared to existing barcoding technology and the lack of empirical evidence to support one’s superiority over the other. Reference is drawn to the way in which RFID and barcoding tech- nologies are represented in the literature. Time and motion studies were conducted in a distribution company’s chilled warehouse where RFID technology had already been trialled and implemented on recyclable refrigerated food trays and in operation alongside barcoding systems. Attention was given to recording the number and nature of errors that each technology exhibited. This paper concludes that while RFID can deliver improved operational performance over tradi- tional barcode systems, it is found to be less reliable in implementation. Hybrid systems may offer operational benefits over single-technology systems, but the cost of their complexity still needs to be examined

Potential effects of RFID technology on internal RTIs' supply chain performance : a case study of "Swire Oilfield Services"

Confidential until 23 May 202