A simple and efficient approach to barcode localization

Kutiyanawala, Aliasgar; Qi, Xiaojun; Tian, Jinshou

doi:10.1109/icics.2009.5397472

Cited by 7 publications

(4 citation statements)

References 11 publications

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“…There are many researchers contribute to the recognition of Barcode. Kutiyanawala, A. propose an approach to localizing the barcode regions, which apply the multichannel Gabor filtering technique to extract eight directional texture features, then apply a randomized hierarchical search strategy to find a sufficient number of pairs lines segments, finally they employ the histogram analysis technique to localize the barcode regions [2]. Hu.…”

Section: Introductionmentioning

confidence: 99%

A System of QR Barcode Recognition Based on Mobile Phone

Yang

Zhang

2012

AMM

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Section: Introductionmentioning

confidence: 99%

A System of QR Barcode Recognition Based on Mobile Phone

Yang

Zhang

2012

AMM

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“…In the following paragraphs we will discuss previous approaches proposed to locate the barcode. Methods based on Spatial Domain are those that search for set of dark lines on white background and that also have strong directional continuity at a specific angle so as to locate barcodes [3]. Katona et al [5] detected the barcodes based on the basic morphological.…”

Section: Previous Workmentioning

confidence: 99%

Autonomous Recognition System for Barcode Detection in Complex Scenes

Chen

Zhang

et al. 2017

ITM Web Conf.

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Linear barcode technology has been widely used in our common life, such as in logistics, retailed products and many other applications. Many researches and smart applications focus on how to decode the barcode so that it is difficult to locate precisely when the background becomes very complex. Moreover, many smart apps need human interaction to make sure the detected region is in a correct position of the screen. This paper presents an effective approach to locate the barcodes in real-time without manual disturbing. Basic morphological operations and Parallel Line Segment Detector (P-LSD) are applied to achieve the legal block of barcodes. Our method has been evaluated by a standard database and the experimental results show that our approach is more robuster than other earlier methods.

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“…They can be used to detect stripe patterns at any orientation and scale. Concrete examples in localization include [11,14]. These methods offer scale and rotation invariance but tend to be slow.…”

Section: Localization Of 1d Barcodesmentioning

confidence: 99%

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

Sörös

Flörkemeier

2013

Proceedings of the 12th International Conference on Mobile and Ubiquitous Multimedia

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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.

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A simple and efficient approach to barcode localization

Cited by 7 publications

References 11 publications

A System of QR Barcode Recognition Based on Mobile Phone

A System of QR Barcode Recognition Based on Mobile Phone

Autonomous Recognition System for Barcode Detection in Complex Scenes

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

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