• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.55-64
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• 2013

Due to the popularization of digital high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy for anyone to make a high-quality counterfeit money. However, the probability of detecting a counterfeit money to the general public is extremely low. In this paper, we propose a counterfeit money detection algorithm using a general purpose scanner. This algorithm determines counterfeit money based on the different features in the printing process. After the non-local mean value is used to analyze the noises from each money, we extract statistical features from these noises by calculating a gray level co-occurrence matrix. Then, these features are applied to train and test the support vector machine classifier for identifying either original or counterfeit money. In the experiment, we use total 324 images of original money and counterfeit money. Also, we compare with noise features from previous researches using wiener filter and discrete wavelet transform. The accuracy of the algorithm for identifying counterfeit money was over 94%. Also, the accuracy for identifying the printing source was over 93%. The presented algorithm performs better than previous researches.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.365-371
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• 2011

Most recently issued paper money includes security patterns that can be only identified by ultra violet (UV) illuminations. We propose an automatic extraction method of UV patterns for paper money inspection systems. The image acquired by camera and UV illumination is transformed to input data through preprocessing. And then, the Gaussian mixture model (GMM) and split-and-merge expectation maximization (SMEM) algorithm are applied to segment the image represented by input data. In order to extract the UV pattern from the segmented image, we develop a criterion using the area of covariance vector and the weight value. The experimental results on various paper money are presented to verify the usefulness of the proposed method.

• Vending industry
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• v.6 no.3 s.18
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• pp.26-28
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• 2006

최근 자판기 시장의 최대 관심사는 내년도 새로운 1000원권 발행에 따른 시장특수가 얼마만큼 이어질수 있느냐 여부이다. 기계 메이커는 기존 필드에 설치된 자판기들의 활발한 대체수요에 큰 기대를 걸고 있고, 관련 지폐식별기 업체들은 국가 발권정책의 변화로 인해 찾아온 천재일우의 기회를 놓치지 않겠다고 사활을 건 총력전을 준비하고 있다. 이러한 가운데 국내 화폐인식장치 시장의 최대 업체인 씨케이테크놀로지가 어떤 제품으로 시장공략을 진행할 지가 첨예의 관심사가 아닐 수 없다. 과연 명성에 걸맞는 최고의 제품으로 신권 교체시장의 니즈를 만족 시킬 수 있을까. 심혈을 기울인 개발 끝에 최근 베일을 벗은 신권 대응 지폐식별기를 공개한다.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2005.11a
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• pp.185-188
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• 2005

XTT assay와 SRB assay를 이용하여 Hep3B와 L929 세포에서 생활하수처리장과 농공단지폐수처리장 방류수의 세포독성을 알아본 결과 다음과 같은 결론을 얻었다. 1) XTT, SRB 실험법에 적용하여 대표적인 발암성 물질인 Benzo(a)Pyrene의 세포독성을 평가 할 수 있었다. Benzo(a)Pyrene 30uM농도는 Hep 3B와 L929 세포에서 약 50%의 세포독성을 나타내었다. 2) 단백질합성과 세포호흡의 활성도로 세포독성을 평가할 수 있는 실험법인 XTT와 SRB 실험법에 적용하여 방류수를 추출 농축한 실제 시료에 대한 세포독성을 평가할 수 있었다. 3) 생활하수처리장의 방류수에 비해 다종 고농도의 화학물질로 오염되어있는 농공단지폐수처리장 방류수에서의 독성발현이 더 높았다. 4) 생활하수처리장 방류수와 농공단지폐수처리장 방류수 중 오염도가 가장 심각한 4지점의 화학물질 분석 결과와 in vitro bio-assay에 의한 세포독성 결과가 일치하였다.

• Vending industry
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• v.6 no.3 s.18
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• pp.48-52
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• 2006

내년 1월 22일은 자판기 산업계에 있어 실로 의미심장한 날이다. 자판기 산업계에 큰 파장을 불러올 새로운 1000원권이 발행되기 때문이다. 신1000원권의 발행을 보는 자판기 산업계의 시각은 각자 틀리다. 지폐식별기 부품업체에 있어서는 천재일우의 시장 특수에 대한 기대에 가슴이 한껏 설레고 있다. 자판기 제조업체 역시도 내년 시장의 자판기 대체수요의 활성화와 지폐식별기 교체시장 특수에 은근한 기대를 걸고 있다. 반면 신권유통에 따라 매상감소를 우려하는 운영업자들은 비상이다. 매상감소는 물론 기계 교체비용에 대한 부담도 적지 않으니 신1000원 발행을 원망하는 분위기이다. 누구에게는 기회이고 누구에게는 위기로 다가올 신권발행의 빛과 그림자이다. 하지만 분명한것은 신 1000원권의 발행은 기정 사실이고 이 교체시장을 잘 넘겨야 한다는 사실이다. 싫든 좋든 현실을 받아 들여 산업계의 피해를 최소화하고 가능한 한 산업 활성화의 계기로 삼는 현명한 대처가 절실한 시점이다. 신1000원권 발행의 특급 호재에 가슴 설레는 지폐식별기 교체 시장 동향을 담아 봤다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.257-258
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• 2024

현재 시각장애인들이 현금을 사용하게 될 시 지폐가 얼마인지 확인할 방법이 없어 불편을 겪거나 금전적 사기를 당할 위험이 잦다. 한국은행에서는 이러한 사고를 막기 위해 점자 지폐를 만들어 발부하고 있지만 시각장애인 91%가 식별하지 못해 많은 불편을 겪고 있다. 본 논문에서는 딥러닝을 활용하여 화폐를 인식하고 TTS 기술을 사용하여 지폐의 값이 얼마인지 소리로 알려주는 시스템을 개발하였다. 지폐 인식을 위해 데이터를 직접 수집하여 YOLOv5 알고리즘을 활용하여 학습시킨 Weights 파일을 사용하였다. 이를 활용하여 시각장애인들은 더 안전하게 현금을 사용하고, 금전적인 문제를 예방할 수 있다.

• Tuberculosis and Respiratory Diseases
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• v.48 no.4
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• pp.438-447
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• 2000

Background : Transbronchial lung biopsy (TBLB) is a relatively simple and convenient procedure to obtain lung tissue from a patient with diffuse or localized lesion on chest radiographs, whose disease cannot be diagnosed through routine tests. The authors tried to evaluate the diagnostic value of TBLB, especially, the concordance between CT scan and TBLB with respect to the location of the lesion and diagnostic yield according to tumor-bronchus relationship. Method : We reviewed the medical records, plain chest films, and chest CT scans of 278 patients who underwent TBLB at Kyungpook National University Hospital between January 1996 and June 1998. Results : One hundred and sixteen (41.7 %) patients were diagnosed by TBLB. Diagnostic yield of TBLB of malignant tumors tended to be higher than that of benign diseases (64.7% versus 53.9%, p=0.09). Of primary lung cancers, TBLB was more diagnostic in adenocarcinoma and small-cell carcinoma than other cell types (p<0.01) and, of benign diseases, more diagnostic in tuberculosis than in non-tuberculous diseases (p<0.05). There was no significant difference in the diagnostic rate according to the location of the tumor. The diagnostic rate tended to increase with the size of tumor (p=0.06). The diagnootic rate of TBLB did not differ according to the pattern of lesion in benign diseases. However, in malignant diseases TBLB was more diagnostic in diffuse/multiple nodular lesions than in localized lesions(p<0.05). According to the tumor-bronchus relationship, TBLB was more diagnootic in type I/II groups than in other types. CT scan and TBLB showed a strong correlation with respect to the localization of the lesion (r=0.994, p<0.01). Conclusion : The above results show that TBLB is useful in the diagnosis of lung disease. CT scan and TBLB showed a strong correlation in determining the location of the lesion. Diagnostic yield of TBLB is higher in lesions with 'bronchus sign' (type I and II). TBLB and other diagnootic methods such as transthoracic needle aspiration are expected to complement one another in the diagnosis of lung diseases.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.889-898
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• 2013

Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

• Journal of Digital Convergence
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• v.11 no.8
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• pp.191-197
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• 2013

In this paper, we implemented a paper currency recognition system using IR(infrared) sensor. The system has 32 channel IR sensor to measure the reflection and penetration quantity of light. The IR image of paper currency of 10-bit gray scale is used to differentiate the real and counterfeit paper currency with image information from 0 to 4095. The characteristics of IR image are recognized by brightness and darkness and the positions of bright and dark portions are different between real and counterfeit paper currency. The price of IR sensors were relatively high, however, it is good price in these days due to mass production to apply to counterfeit detection area. We used a software table having the IR characteristics of real paper currency to compare with the IR images of the input paper currency. The performance of the implemented system shows 1-2% error rates for Euro real paper currency and 0% error rates for various counterfeit paper currencies of several countries.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.471-480
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• 2002

In this paper, we implemented a real-time system improving the performance of the paper currency discrimination by integrating a weighted region of interest matching algorithm with a weighted shape feature matching algorithm of the blocked image. The system classifies the paper currency by comparing a query image with compared images based on the database that contain images of paper currency. Especially, the system has good efficiency at the contaminated, rotated, and translated paper currency. The system hardware consists of three parts as follows : the paper currency image acquired by CIS(contact image sensor) is applied to the pre-processing part with A/D converter and PLD. Finally the pre-processed image data are classified by the main image processing part with a high-speed DSP based on the proposed algorithm.