Efficient 1D and 2D barcode detection using mathematical morphology

Barcode technology is essential in automatic identification, and is used in a wide range of real-time applications. Different code types and applications impose special problems, so there is a continuous need for solutions with improved performance. Several methods exist for code localization, that are well characterized by accuracy and speed. Particularly, high-speed processing places need reliable automatic barcode localization, e.g. conveyor belts and automated production, where missed detections cause loss of profit. Our goal is to detect automatically, rapidly and accurately the barcode location with the help of extracted image features. We propose a new algorithm variant, that outperforms in both accuracy and efficiency other detectors found in the literature using similar ideas, and also improves on the detection performance in detecting 2D codes compared to our previous algorithm

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

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

Survey of KI, WU, MW and STL polyomavirus in cancerous and non-cancerous lung tissues

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An approach to the quantitative assessment of retinal layer distortions and subretinal fluid in SD-OCT images

A modern tool for age-related macular degeneration (AMD) investigation is Optical Coherence Tomography (OCT), which can produce high resolution cross-sectional images of retinal layers. AMD is one of the most frequent reasons for blindness in economically developed countries. AMD means degeneration of the macula, which is responsible for central vision. Since AMD affects only this specific part of the retina, untreated patients lose their fine shape- and face recognition, reading ability, and central vision. Here, we deal with the automatic localization of subretinal fluid areas and also analyze retinal layers, since layer information can help to localize fluid regions. We present an algorithm that automatically delineates the two extremal retinal layers, successfully localizes subretinal fluid regions, and computes their extent. We present our results using a set of SD-OCT images. The quantitative information can also be visualized in an anatomical context for visual assessment

Synthesis of Novel Aromatic Core Zero Generation Dendrimers

Bromomethyl arenes used as polyfunctional core of dendrimers were derivatized with diethanolamine branches. The obtained compounds containing 4 or 6 hydroxyl terminal surface groups are highly water-soluble