• 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.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.203-203
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• 2004

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.109-110
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• 2012

In this paper, we propose an adaptive thresholding method to binarize two-dimensional barcode images. Adaptive thresholding methods are applied to document image binarization. Thus, they inappropriate to use in recognition of two-dimensional barcode images. To overcome the problem, we propose a new adaptive threshold method using the integral image. To show the effectiveness of our method, we compared our method with the well-known existing method in terms of visual quality and processing time. The experimental result indicates that the proposed method is superior to the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2453-2458
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• 2012

In this paper, we propose an adaptive thresholding method to binarize two-dimensional barcode images. Adaptive thresholding methods that minimize light effects convert an original image into a binary image. The methods are applied to document image binarization. The methods, however, have problems of determining box size used in adaptive thresholding. thus, they inappropriate to use in recognition of two-dimensional barcode images. To overcome the problem, we analysis the problem and propose a new adaptive threshold method using the integral image. To show the effectiveness of our method, we compared our method with the well-known existing methods in terms of visual quality and processing time. The experimental result indicates that the proposed method is superior to the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.276-281
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• 2019

Food printers must use food ink cartridges approved by the Ministry of Food and Drug Safety (MFDS). A 2D bar code is used to read whether the ink cartridge is authentic. However, since the dye is diverged by heat pressure and printed, the barcode is contaminated. In this paper, we propose a pre-processing algorithm to solve the problem of barcode contamination by food coloring dust in a latte art printer. The algorithm is based on various morphological operations. We apply this algorithm before reading contaminated barcode images with a general QR code reader. It has been confirmed that, as compared with the existing QR code reader, the contamination rate that can be perceived is increased from 25% to 40% and even at a contamination rate of 45%, the recognition rate reaches 50%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.161-170
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• 2019

Multi-product mass production small and medium enterprise factories have a wide variety of products and a large number of products, wasting manpower and expenses for inventory management. In addition, there is no way to check the status of inventory in real time, and it is suffering economic damage due to excess inventory and shortage of stock. There are many ways to build a real-time data collection environment, but most of them are difficult to afford for small and medium-sized companies. Therefore, smart factories of small and medium enterprises are faced with difficult reality and it is hard to find appropriate countermeasures. In this paper, we implemented the contents of extension of existing inventory management method through character extraction on label with barcode and QR code, which are widely adopted as current product management technology, and evaluated the effect. Technically, through preprocessing using OpenCV for automatic recognition and classification of stock labels and barcodes, which is a method for managing input and output of existing products through computer image processing, and OCR (Optical Character Recognition) function of Google vision API. And it is designed to recognize the barcode through Zbar. We propose a method to manage inventory by real-time image recognition through Raspberry Pi without using expensive equipment.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.558-561
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• 2009

In this paper, we propose Simple Frame Marker(SFMarker) to support recognition of characters and images included in a marker in augmented reality. If characters are inserted inside of marker and are recognised using Optical Character Recognition(OCR), it doesn't need marker learning process before an execution. It also reduces visual disturbance compared to 2D barcode marker due to familarity of characters. Therefore, proposed SFMarker distinguishes Square SFMarker that embeds images from Rectangle SFMarker with characters according to ratio of marker and applies different recognition algorithms. Also, in order to reduce preprocessing of character recognition, SFMarker inserts direction information in border of marker and extracts it to execute character recognition fast and correctly. Finally, since the character recognition for every frame slows down tracking speed, we increase the speed of recognition process using the result of character recognition in previous frame when frame difference is low.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.733-736
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• 2009

In this paper, we proposed the coupon recognition system using vision techniques. In the proposed system coupon information represented by the ID in the database. We use the camera to acquire images which contains coupon information. By using the ID we get information from the database. The performance of proposed system is verified through many mobile phones.

• Journal of IKEEE
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• v.6 no.1 s.10
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• pp.10-20
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• 2002

The purpose of this work is to develop a system fer rapid and automatic identification of persons, with high reliability and confidence levels. The iris of the eye is used as an optical fingerprint, having a highly detailed pattern that is unique for each individual and stable over many years. Image analysis algorithms find the iris in a image, and encode its texture into an iris code. Iris texture is extracted from the image at multiple scales of analysis by wavelet transformation. The features of many different parts of the iris are projected onto the space-frequency space. They are used to determine an abstract iris code which is similar to 2D barcode. Pattern recognition is achieved by using modified CPN.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.74-79
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• 2009

Fiducial markers have been used frequently in augmented reality applications. However, they represent only ID information to identify a marker, and thus they have limitations when we have multiple types of markers. In this paper, we propose a new marker design for augmented reality applications. We embed a marker’s context, such as type, size, orientation, and ID, in the barcode that has been used just for storing an ID. BY embedding the context information, it is possible to recognize multiple types of markers at once and to render corresponding contents with proper scale. Our marker design can be used in a mobile augmented reality environment where many unknown types of markers may exist.