• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.276-276
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• 2013

Here we report an integrated microdevice consisting of an efficient passive mixer, a magnetic separation chamber, and a capillary electrophoretic microchannel in which DNA barcode assay, target pathogen separation, and barcode DNA capillary electrophoretic analysis were performed sequentially within 30 min for multiplex pathogen detection at the single-cell level. The intestine-shaped serpentine 3D micromixer provides a high mixing rate to generate magnetic particle-pathogenic bacteria-DNA barcode labelled AuNP complexes quantitatively. After magnetic separation and purification of those complexes, the barcode DNA strands were released and analyzed by the microfluidic capillary electrophoresis within 5 min. The size of the barcode DNA strand was controlled depending on the target bacteria (Staphylococcus aureus, Escherichia coli O157:H7, and Salmonella typhimurium), and the different elution time of the barcode DNA peak in the electropherogram allows us to recognize the target pathogen with ease in the monoplex as well as in the multiplex analysis. In addition, the quantity of the DNA barcode strand (~104) per AuNP is enough to be observed in the laser-induced confocal fluorescence detector, thereby making single-cell analysis possible. This novel integrated microdevice enables us to perform rapid, sensitive, and multiplex pathogen detection with sample-in-answer-out capability to be applied for biosafety testing, environmental screening, and clinical trials.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1506-1508
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• 2015

A 2D barcode region localization system for the automatic inspection of a long distance logistics objects has been developed. For the successful 2D barcode localization, variance and frequency of the pixel distribution within average 2D barcodes is modeled and the average model of 2D barcode is combined with the corner features detection to localize the final 2D barcode candidates. An automatic 2D barcode localization software was developed with the multiple features mixture method and we tested our system on real camera images of several popular 2D barcode symbologies.

• Journal of KIISE
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• v.42 no.7
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• pp.868-877
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• 2015

The barcode area extraction from images has been extensively studied, and existing methods exploit frequency characteristics or depend on the Hough transform (HT). However, the slantedness of the images and noise affects the performance of these approaches. Moreover, it is difficult to deal with the case where an image contains multiple barcodes. We therefore propose a barcode detection algorithm that is robust under such unfavorable conditions. The pre-processing step implements a probabilistic Hough transform to determine the areas that contain barcodes with a high probability, regardless of the slantedness, noise, and the number of instances. Then, a frequency component analysis extracts the barcodes. We successfully implemented the proposed system and performed a series of barcode extraction tests.

• Journal of Digital Convergence
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• v.13 no.2
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• pp.159-175
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• 2015

The two-dimensional QR code has advantages such as directional nature, enough data storage capacity, ability of error correction, and ability of data restoration. There are two major issues like speed and correctiveness of recognition in the two-dimensional QR code. Therefore, this paper proposes a morphology-based algorithm of detecting the interest region of a barcode. Our research contents can be summarized as follows. First, the interest region of a barcode image was detected by close operations in morphology. Second, after that, the boundary of the barcode are detected by intersecting four cross line outside in a code. Three, the projected image is then rectified into a two-dimensional barcode in a square shape by the reverse-perspective transform. In result, it shows that our detection and recognition rates for the barcode image is also 97.20% and 94.80%, respectively and that outperforms than previous methods in various illumination and distorted image environments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1865-1867
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• 2007

We propse a novel corner detection algorithm for locating 2D Data Matrix barcode in an image. The proposed method accumulates weight for each cross point defined by every combination of edge points in the image, and detects the corner point of the barcode L-pattern by determining the location of the highest accumulated weight. By designing the weight considering the connectivity of two lines around the cross point, we were able to detect the corner of L-pattern even for the cases that the lines of L-patterns are short. In the experiments, the proposed method showed improved performance compared with the conventional Hough transform based method in terms of detectability and computation time.

• Journal of the Semiconductor & Display Technology
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• v.8 no.2
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• pp.23-29
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• 2009

To increase the data capacity of one-dimensional symbology, 2D barcodes have been proposed a decade ago. In this paper, a new 2D barcode detection algorithm based on Local Binary Pattern is presented. To locate 2D barcode symbols, a texture analysis scheme based on the Local Binary Pattern is adopted, and a gray-scale projection with sub-pixel operation is utilized to separate the symbol precisely from the input image. Finally, the segmented symbol is normalized using the inverse perspective transformation for the decoding process. The proposed method ensures high performances under various lighting/printing conditions and strong perspective deformations. Experiments show that our method is very robust and efficient in detecting the symbol area for the various types of 2D barcodes.

• Journal of the Korea Convergence Society
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• v.6 no.1
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• pp.7-16
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• 2015

A segmentation process extracts an interesting area of barcode in an image and gives a crucial impart on the performance of barcode verifier. Previous segmentation methods occurs some issues as follows. First, it is very hard to determine a threshold of length in Hough Line transform because it is sensitive. Second, Morphology transform delays the process when you conduct dilation and erosion operations during the image extraction. Therefore, we proposes a novel Converged Harris Corner detection-based segmentation method to detect an interesting area of barcode in Data Matrix. In order to evaluate the performance of proposed method, we conduct experiments by a dataset of barcode in accordance with size and location in an image. In result, our method solves the problems of delay and surrounding environments, threshold setting, and extracts the barcode area 100% from test images.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.259-268
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• 2008

In an effort to increase the data capacity of one-dimensional symbology, 2D barcodes have been proposed a decade ago. In this paper, we present an effective 2D barcode detection algorithm from gray-level images, especially for the handheld 2D barcode recognition system. To locate the symbol inside the image, a criteria based on the block contrast is adopted, and a gray-scale projection with sub-pixel operation is utilized to segment the symbol precisely from the region of interest(ROI). Finally, the segmented ROI is normalized using the inverse perspective transformation for the following decoding processes. We also introduce the post-processing steps for decoding the QR-code. The proposed method ensures high performances under various lighting/printing conditions and strong perspective deformations. Experiments shows that our method is very robust and efficient in detecting the code area for the various types of 2D barcodes in real time.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2563-2573
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• 1999

In most mail automatic processing centers, after facing and canceling, letter mails are passed through an Optical Character Recognition/Barcode Sorter(OCR/BS) to read the postal code and 3 of 5 fluorescent (luminescent) barcode is applied. Normally, 31%∼35% of this mails are rejected. The main reasons for reading failures are poor printing quality of addresses and barcodes, script printing, writing in a cursive hand, variety fonts, and failure to locate the address. Our goal is to provide mailer with top quality service and customer barcode service as we move toward 100% barcoding automation of letter mail. In this paper, we propose a method of printing 3 of 5 customer barcode, postal code management, and detection of postal code based on postal address for increase the performance of automatic processing system in mail items. Using postal code generating rules, which are automatically extracted from postal addresses and address numbers, creates postal codes. The customer barcode support system is implemented by C++ language and runs on IBM PC under Windows 95.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2121-2128
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• 2015

In this paper presents a method of extracting reliable and regions of interest (ROI) in barcode for the purpose of factory automation. backgrounds are separated based on directional components and the characteristics of detected patterns. post-processing is performed on candidate images with analysis of problems caused by blur, rotation and areas of high similarity. In addition, the resizing factor is used to achieve faster calculations through image resizing. The input images contained multiple product or barcode for application to diverse automation environments; a high extraction success rate is accomplished despite the maximum shooting distance of 80 cm. Simulations involving images with various shooting distances gave an ROI detection rate of 100% and a post-processing success rate of 99.3%.