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

2D Color Code Interference Cancellation by Super Imposing Methodology

Abstract-Today the 2-D barcodes have become more popular for information embedding. To encode information with high spatial density while ensuring robust reading by an optical system is the main goal of a barcode system. To enhance the density of information, different ink colors could be used. A High Capacity Color Barcode framework is proposed by exploiting the spectral diversity afforded by the Cyan, Magenta, Yellow print colorant channels and the complimentary Red, Green and Blue channels, respectively, used for capturing color images. Here a three-fold increase in the data rate is achieved by encoding independent data in the C, M, and Y print colorant channels and decoding the data from the complimentary R, G, and B channels captured via a mobile phone camera. This paper presents a framework of color barcode for mobile phone applications by exploiting the spectral diversity afforded by the cyan (C), magenta (M), and yellow (Y) print colorant channels which is more commonly used for color printing and the complementary in order to red (R), green (G), and blue (B) channels, respectively, used for capturing color images. In this paper the system exploit this spectral diversity to understand three-fold increase in the data rate by encoding independent data in the C, M, and Y print colorant channels and decoding the data from the complementary R, G, and B channels captured via a mobile phone camera. To mitigate the effect of cross-channel interference among the print colorant and capture color channels, the system develops an algorithm for interference cancellation which is based on a physically-motivated mathematical model for the print and capture processes. To collect the model parameters which are necessary for cross-channel interference cancellation, this scheme proposes a super imposing methodology. Experimental result clears that the scheme framework successfully overcomes the impact of the color interference, providing a low bit error rate and a high decoding rate for each of the colorant channels when used with a corresponding error correction scheme

The Evolution of First Person Vision Methods: A Survey

The emergence of new wearable technologies such as action cameras and smart-glasses has increased the interest of computer vision scientists in the First Person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with First Person Vision recording capabilities. Due to this interest, an increasing demand of methods to process these videos, possibly in real-time, is expected. Current approaches present a particular combinations of different image features and quantitative methods to accomplish specific objectives like object detection, activity recognition, user machine interaction and so on. This paper summarizes the evolution of the state of the art in First Person Vision video analysis between 1997 and 2014, highlighting, among others, most commonly used features, methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart Glasses, Computer Vision, Video Analytics, Human-machine Interactio

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

Understand Biology Using Single Cell RNA-Sequencing

This dissertation summarizes the development of experimental and analytical tools for single cell RNA sequencing (scRNA-Seq), including 1) scPLATE-Seq, a FACS- and plate-based scRNASeq platform, which is accurate, robust, fully automated and cost-efficient; 2) metaVIPER, an algorithm for transcriptional regulator activity inference based on scRNA-Seq profiles; and 3) iterClust, a statistical framework for iterative clustering analysis, especially suitable for dissecting hierarchy of heterogeneity among single cells. Further this dissertation summarizes biological questions answered by combining these tools, including 1) understanding inter- and intra-tumor heterogeneity of human glioblastoma; 2) elucidating regulators of β-cell de-differentiation in type-2 diabetes; and 3) developing novel therapeutics targeting cell-state regulators of breast cancer stem cells

Computational Topology Techniques for Characterizing Time-Series Data

Topological data analysis (TDA), while abstract, allows a characterization of time-series data obtained from nonlinear and complex dynamical systems. Though it is surprising that such an abstract measure of structure - counting pieces and holes - could be useful for real-world data, TDA lets us compare different systems, and even do membership testing or change-point detection. However, TDA is computationally expensive and involves a number of free parameters. This complexity can be obviated by coarse-graining, using a construct called the witness complex. The parametric dependence gives rise to the concept of persistent homology: how shape changes with scale. Its results allow us to distinguish time-series data from different systems - e.g., the same note played on different musical instruments.Comment: 12 pages, 6 Figures, 1 Table, The Sixteenth International Symposium on Intelligent Data Analysis (IDA 2017

Tag detection for preventing unauthorized face image processing

A new technology is being proposed as a solution to the problem of unintentional facial detection and recognition in pictures in which the individuals appearing want to express their privacy preferences, through the use of different tags. The existing methods for face de-identification were mostly ad hoc solutions that only provided an absolute binary solution in a privacy context such as pixelation, or a bar mask. As the number and users of social networks are increasing, our preferences regarding our privacy may become more complex, leaving these absolute binary solutions as something obsolete. The proposed technology overcomes this problem by embedding information in a tag which will be placed close to the face without being disruptive. Through a decoding method the tag will provide the preferences that will be applied to the images in further stages