• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.35-43
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• 2004

In this paper, we proposed a vehicle recognition and electronic toll collection system with detection and classification of vehicle identification mark and emblem as well as recognition of vehicle license plate to unman toll fee collection system or incoming/outcoming vehicles to an institution. In the proposed algorithm, we first process pre-processing step such as noise reduction and thinning from the rear side input image of vehicle and detect vehicle mark, emblem and license plate region using intensity variation informations, template masking and labeling operation. And then, we classify the detected vehicle features regions into vehicle mark and emblem as well as recognize characters and numbers of vehicle license plate using hybrid and seven segment pattern vector. To show the efficiency of the proposed algorithm, we tested it on real vehicle images of implemented vehicle recognition system in highway toll gate and found that the proposed method shows good feature detection/classification performance regardless of irregular environment conditions as well as noise, size, and location of vehicles. And also, the proposed algorithm may be utilized for catching criminal vehicles, unmanned toll collection system, and unmanned checking incoming/outcoming vehicles to an institution.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.146-155
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• 2000

This paper describes a 4-state bar code called HANGUL 4 ST that has been specifically designed for automatic processing of the letter mails, A HANGUL 4 ST bar code is a necessary data base that is applied data capture and data carrier with it all the information necessary for sorting, the amount capture for transportation of mail items, and valued-added services such as indicia, tracking and trace. The 4-state bar code information contents are composed of a postal code, delivery point, customer information including customer identification number and name, and parity bits for error detect and correct. The data density capability of HANGUL 4 St allows all useful sorting data and customer data to be encoded on one label. This supports better automatic processing in mail items, higher level of customer service and more efficient operation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.1
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• pp.47-53
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• 2007

Satellite image mosaicking is essential for image interpretation and analysis especially for a large area such as the Korean Peninsula. This paper proposed the technique of automatic seam-line extraction and the method of creating image mosaic in automated fashion. The seam-line to minimize artificial discontinuity was extracted using Minimum Absolute Gray Difference Sum algorithm with constraint condition on search-area width and Canny Edge Detection algorithm. To maintain the radiometric balance among images acquired at different time epochs, we utilized Match Cumulative Frequency method. Experimental results showed that edge detection algorithm extracted the seam-lines significantly well along linear features such as roads and rivers.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.169-175
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• 2011

In this paper, an automatic scoring system of the OMR answer sheet is implemented using Gray Scale and image segmentation method. The proposed method was used to extract the OMR data on multiple-choice answer sheet from captured image. In addition, On-line scoring system is developed and implemented to mark the short-answer type on the reverse side. Therefore, teachers can mark the short-answer type for anytime and anywhere within the available time. There were many advantages to mark of the multiple-choice answer sheet without additional OMR reader. In the future, the grading of short-answer type will be more efficient if it were performed by using an automatic scoring system based on image processing.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.201-202
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• 2008

난청은 가장 흔한 선천성 장애이다. 이 질병의 발생 빈도는 신생아 1000명 출생 당 $1{\sim}3$명 정도로 상당히 높다. 이러한 청력 장애가 조기에 발견된다면 수술적인 치료 등으로 예방할 수 있으나 그렇지 못할 경우 언어와 학습장애를 초래하게 된다. 이런 관점을 근거로 신생아를 대상으로 한 선천성 난청의 선별검사는 큰 의미를 가지며 난청환자의 조기발견을 위한 노력이 필수적이라 할 수 있다. 기존의 수동 청력검사 시스템은 신생아 청력 평가시 검사자의 주관성에 의존하게 되므로, 청성뇌간 반응의 뇌파분석이 잘못될 가능성이 커진다. 따라서 본 연구에서는 청력 역치를 자동으로 판독하여 결과를 나오도록 개발하고자 하였으며, 또한 기존 제품들과는 차별화하여 휴대용으로 개발하여 차폐실이 아닌 일반 병실에서도 검사가 가능하도록 함에 따라 유소아의 청각 장애를 극복시키는데 기여하고자 하였다.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.25-34
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• 2017

Autoencoder is a type of deep learning method where input layer and output layer are the same, and effectively extracts and restores characteristics of input vector using constraints of hidden layer. In this paper, we propose methods of Autoencoders to remove a natural background image which is a noise to the CAPTCHA and recover only a numerical images by applying various autoencoder models to a region where one number of CAPTCHA images and a natural background are mixed. The suitability of the reconstructed image is verified by using the softmax function with the output of the autoencoder as an input. And also, we compared the proposed methods with the other method and showed that our methods are superior than others.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.61-66
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• 2003

The change detection using the satellite imagery and airphotos has been carried out in the application of terrain mapping, environment, forestry, facility detection, etc. The low-spatial resolution data such as Landsat, NOAA satellite images is generally used for automatic change detection, while on the other hand the high-spatial resolution data is used for change detection by image interpretation. The research to integrate automatic method with manual change detection through the high-spatial resolution satellite image is performed. but the problem such as shadow, building 'lean' due to perspective geometry and precision geocorrection was found. In this paper we performed change detection using the IKONOS satellite images, and present the concerning problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.344-346
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• 2016

FHIR is a protocol that enables easy data exchange from the time the event occurred in health care settings as a standard for next-generation message exchange of HL7. Create a meaningful message from the ECG and medical equipment, and express the messages generated by standardized FHIR message it will be used in various medical institutions to ensure delivery to EMR, such as hospital information systems can query the results via a smartphone. In addition, it thought to be used in the future to expand SMART on FHIR, Cardiology, Cardiovascular Surgery ward in real-time remote monitoring.

• Smart Media Journal
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• v.11 no.9
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• pp.47-55
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• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.100-107
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• 2007

AABR(automated auditory brainstem response) test is used for the screening purpose of hearing ability of neonates. In this paper, algorithm using Rolle's theorem is suggested for automatic detection of the ensemble averaged ABR waveform. The ABR waveforms were recorded from 55 normal-hearing ears of neonates at screening levels varying from 30 to 60 dBnHL. Recorded signals were analyzed by expert audiologist and by the proposed algorithm. The results showed that the proposed algorithm correctly identified latencies of the major ABR waves (III, V) with latent difference below 0.2 ms. No significant differences were found between the two methods. We also analyzed the ABR signals using derivative algorithm and compared the results with proposed algorithm. The number of detected candidate waves using the proposed algorithm was 47 % less than that of the existing one. The proposed method had lower relative errors (0.01 % error at 60dBnHL) compared to the existing one. By using proposed algorithm, clinicians can detect and label waves III and V more objectively and quantitatively than the manual detection method.