• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.1
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• pp.197-205
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• 2007

We have proposed a novel line detection method based on the estimated probability density function of gradient directions of edges. By estimating peaks of the density function, we determine groups of edges that have the same gradient direction. For edges in the same groups, we detect lines that correspond to peaks of the connectivity weighted distribution of the distances from the origin. In the experiments using the Data Matrix barcode images and LCD images, the proposed method showed better performance than conventional Methods in terms of the processing speed and accuracy.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2092-2095
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• 2003

In this paper, we propose an algorithm to extract rectangular object area such 3s Data Matrix two-dimensional barcode using edge tracing-based linear feature detection. Hough transform is usually employed to detect lines of edge map. However, it requires parametric image space, and does not find the location of end points of the detected lines. Our algorithm detects end points of the detected lines using edge tracing and extracts object area using its shape information.

• 한국균학회소식:학술대회논문집
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• 2015.11a
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• pp.41-41
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• 2015

Oomycetes belong to the kingdom Straminipila, a remarkably diverse group which includes brown algae and planktonic diatoms, although they have previously been classified under the kingdom Fungi. These organisms have evolved both saprophytic and pathogenic lifestyles, and more than 60% of the known species are pathogens on plants, the majority of which are classified into the order Peronosporales (includes downy mildews, Phytophthora, and Pythium). Recent phylogenetic investigations based on DNA sequences have revealed that the diversity of oomycetes has been largely underestimated. Although morphology is the most valuable criterion for their identification and diversity, morphological species identification is time-consuming and in some groups very difficult, especially for non-taxonomists. DNA barcoding is a fast and reliable tool for identification of species, enabling us to unravel the diversity and distribution of oomycetes. Accurate species determination of plant pathogens is a prerequisite for their control and quarantine, and further for assessing their potential threat to crops. The mitochondrial cox2 gene has been widely used for identification, taxonomy and phylogeny of various oomycete groups. However, recently the cox1 gene was proposed as a DNA barcode marker instead, together with ITS rDNA. To determine which out of cox1 or cox2 is best suited as universal oomycete barcode, we compared these two genes in terms of (1) PCR efficiency for 31 representative genera, as well as for historic herbarium specimens, and (2) in terms of sequence polymorphism, intra- and interspecific divergence. The primer sets for cox2 successfully amplified all oomycete genera tested, while cox1 failed to amplify three genera. In addition, cox2 exhibited higher PCR efficiency for historic herbarium specimens, providing easier access to barcoding type material. In addition, cox2 yielded higher species identification success, with higher interspecific and lower intraspecific divergences than cox1. Therefore, cox2 is suggested as a partner DNA barcode along with ITS rDNA instead of cox1. Including the two barcoding markers, ITS rDNA and cox2 mtDNA, the multi-locus phylogenetic analyses were performed to resolve two complex clades, Bremia lactucae (lettuce downy mildew) and Peronospora effuse (spinach downy mildew) at the species level and to infer evolutionary relationships within them. The approaches discriminated all currently accepted species and revealed several previously unrecognized lineages, which are specific to a host genus or species. The sequence polymorphisms were useful to develop a real-time quantitative PCR (qPCR) assay for detection of airborne inoculum of B. lactucae and P. effusa. Specificity tests revealed that the qPCR assay is specific for detection of each species. This assay is sensitive, enabling detection of very low levels of inoculum that may be present in the field. Early detection of the pathogen, coupled with knowledge of other factors that favor downy mildew outbreaks, may enable disease forecasting for judicious timing of fungicide applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.911-913
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• 2016

Recently barcode detection using a camera is popular, but the recognition performance is low at the effectively low-resolution. The paper propose sub-pixel synchronization technique for better recognition performance. The experiments with ITF-18 demonstrates its performance gain (66% for CIF, 100% for VGA) against the existing recognition algorithms.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.443-444
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• 2020

본 논문에서는 여러 개의 측방 유동 스트립을 형광분석을 통한 정량분석을 할 수 있는 장비의 각 스트립에 인쇄된 바코드를 카메라를 이용하여 인식하는 방법을 제안한다. 제안한 알고리즘에서는 각 슬롯의 스트립 유무를 판단하고, 시작 비트의 위치를 템플릿 정합법으로 검출하여 바코드 영역을 찾는다. 각 비트 영역은 바코드 설계 데이터와 기기 교정 시 계산된 공간 해상도를 이용하여 결정된다. 각 비트의 값은 비트 영역 중앙 부분의 평균을 이용하여 결정하였다. 다양한 조명 아래에서 취득한 영상들로부터 스트립 유무 판단, 시작 비트 위치 탐색 성공 여부 및 각 비트 값을 결정 등을 위한 판정 값을 가우시안 모델을 이용하여 계산하였다. 실험 결과 모든 판정 오류는 무시할 만 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.1001-1002
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• 2017

2차원 바코드는 1차원 바코드의 데이터 용량의 한계를 극복하여 최근 많이 사용되고 있다. 복잡한 환경에서 바코드의 인식을 위해서는 바코드 영역 검출이 중요한 단계이다. 본 논문에서는 딥러닝 기법을 이용하여 QR코드 검출 시스템을 구현한다. 실험은 실생활에서 카메라로 촬영한 바코드 영상을 이용한다.

• The Korea Journal of Herbology
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• v.39 no.2
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• pp.1-9
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• 2024

Objectives : Paeng-hwal is described as an insect herbal medicine used for digestive diseases in the Dong-ui-bo-gam. The origin of this herbal medicine is limited to several small crabs, such as Helice tridens. These crab species cohabitat in the same environment and share similar morphological characteristics, making it very difficult to distinguish and collect the individual species for use in dietary supplements or herbal medicines. This study was conducted to develop a genetic identification tool for discriminating among these closely related small crab species. Methods : CO1 DNA barcode regions of 15 samples from 6 species of small crabs were analyzed to obtain the individual sequences. To identify the correct species, comparative analyses were carried out using the database of the NCBI GenBank and the NIBR. SCAR primers were designed to develop simple and rapid assay methods using inter-species specific sequences. Optimal SCAR assay conditions were established through gradient PCR, and the limit of detection (LOD) was determined. Results : Six species of small crabs (Helicana tridens, Macrophthalmus abbreviatus, Helicana tientsinensis, Helicana wuana, Chiromantes dehaani, and Hemigrapsus penicillatus), which are distributed as Paeng-hwal, were identified through CO1 sequences analysis. We also developed SCAR markers to distinguish between six small crabs at the species level. Furthermore, we established the optimal PCR assay methods and the LOD of each individual species. Conclusions : The rapid and simple SCAR-PCR assay methods were developed to identify the species and control the quality of herbal medicines for Paeng-hwal based on the genetic analyses of CO1 DNA barcodes.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.176-187
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• 2024

Recently, automated solutions using collaborative robots have been emerging in various industries. Their primary functions include Pick & Place, Peg in the Hole, fastening and assembly, welding, and more, which are being utilized and researched in various fields. The application of these robots varies depending on the characteristics of the grippers attached to the end of the collaborative robots. To grasp a variety of objects, a gripper with a high degree of freedom is required. In this paper, we propose a service automation system using a multi-degree-of-freedom gripper, collaborative robots, and vision sensors. Assuming various products are placed at a checkout counter, we use three cameras to recognize the objects, estimate their pose, and create grasping points for grasping. The grasping points are grasped by the multi-degree-of-freedom gripper, and experiments are conducted to recognize barcodes, a key task in service automation. To recognize objects, we used a CNN (Convolutional Neural Network) based algorithm and point cloud to estimate the object's 6D pose. Using the recognized object's 6d pose information, we create grasping points for the multi-degree-of-freedom gripper and perform re-grasping in a direction that facilitates barcode scanning. The experiment was conducted with four selected objects, progressing through identification, 6D pose estimation, and grasping, recording the success and failure of barcode recognition to prove the effectiveness of the proposed system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.174-183
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• 2011

This paper is about a bar code decoding algorithm developed for smart phone applications. The algorithm consists of bar code data extraction procedure, bar code signal estimation procedure, and bar code decoding procedure. To detect the peak bar code module, a DSTW had been applied because of its outstanding performance in ECG peak detection. In order to minimize errors due to non-uniform light effect, the proposed algorithm was acted as a baseline wandering filter based on module peaks detection. The algorithm had been tested to evaluate the performance under the conditions of blurring, non-uniformed light and white noises. The algorithm had shown excellent performance in reconstruction of bar code decoding, compared to other conventional methods. In order to show the possibility of applying the algorithm to a smart phone, a real UPC-A type 150 bar code pictures obtained from a smart phone camera was applied to the algorithm, achieving the correct recognition rate of 97.33%.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.687-688
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• 2016

복잡한 환경에서 바코드의 인식을 위해서는 바코드 영역 검출이 중요한 단계이다. 본 논문에서는 2차원 바코드 영역 검출 알고리즘을 제안한다. 분산-빈도수와 코너 특징을 이용하여 바코드 후보 영역을 선정한다. 빈도수 계산 시 탐색윈도우의 연결성분을 판단하여 윈도우 크기를 확장하는 방법을 추가하여 이전 연구의 한계점을 개선한다. 이전에 실험한 영상에서 모두 바코드 영역을 검출하였고 이전 연구에서 검출하지 못한 셀의 크기가 큰 바코드 영역을 검출한 것을 확인하였다.