• Journal of Sensor Science and Technology
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• v.15 no.2
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• pp.112-119
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• 2006

Resolution of an image sensor is very significant parameter to improve. It is hard to improve the resolution of the CMOS vision chip for edge detection based on a biological retina using a resistive network because the vision chip contains additional circuits such as a resistive network and some processing circuits comparing with general image sensors such as CMOS image sensor (CIS). In this paper, we proved the problem of low resolution by separating photo-sensing and signal processing circuits. This type of vision chips occurs a problem of low operation speed because the signal processing circuits should be commonly used in a row of the photo-sensors. The low speed problem of operation was proved by using a reset decoder. A vision chip for edge detection with $128{\times}128$ pixel array has been designed and fabricated by using $0.35{\mu}m$ 2-poly 4-metal CMOS technology. The fabricated chip was integrated with optical lens as a camera system and investigated with real image. By using this chip, we could achieved sufficient edge images for real application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1142-1147
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• 2022

The edges of image should be detected first so that the objects in the image can be identified. An hardware-implemented edge detection algorithm outperforms its software version. Sobel operation is the most suitable algorithm for an hardware implementation of edge detection. And lots of works have been done to perform Sobel operations efficiently on FPGA-based hardware. This work proposes how to implement fast edge detection circuit on FPGA, which is based on the conventional circuit for edge detection using Sobel operator. The newly proposed circuit is suitable for processing images when the images are stored in memory devices and outperforms the conventional one with little additional FPGA resources. Both the conventional circuit and the proposed circuit were implemented on an FPGA. And the result showed that the proposed circuit almost doubles the performance in processing images and needs little additional FPGA resources.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.770-775
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• 2023

Recently, as the amount of digital data increases exponentially, the importance of data processing systems is being emphasized. In this situation, the selection and construction of data processing systems are becoming more important. In this study, the performance of cloud computing (CC), edge computing (EC), and UAV-based intelligent edge computing (UEC) was compared as a way to solve this problem. The characteristics, strengths, and weaknesses of each method were analyzed. In particular, this study focused on real-time large-capacity data processing situations such as corridor monitoring. When conducting the experiment, a specific scenario was assumed and a penalty was given to the infrastructure. In this way, it was possible to evaluate performance in real situations more accurately. In addition, the effectiveness and limitations of each computing method were more clearly understood, and through this, the help was provided to enable more effective system selection.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.87-95
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• 2022

Recently, with the development of smart technology, in medical information platform, patient's biometric data is measured in real time and accumulated into database, and it is possible to determine the patient's emergency situations. Medical staff can easily access patient information after simple authentication using a mobile terminal. However, in accessing medical information using the mobile terminal, it is necessary to study authentication in consideration of the patient situations and mobile terminal. In this paper, we studied on medical information platforms based on big data processing and edge computing for supporting automatic authentication in emergency situations. The automatic authentication system that we had studied is an authentication system that simultaneously performs user authentication and mobile terminal authentication in emergency situations, and grants upper-level access rights to certified medical staff and mobile terminal. Big data processing and analysis techniques were applied to the proposed platform in order to determine emergency situations in consideration of patient conditions such as high blood pressure and diabetes. To quickly determine the patient's emergency situations, edge computing was placed in front of the medical information server so that the edge computing determine patient's situations instead of the medical information server. The medical information server derived emergency situation decision values using the input patient's information and accumulated biometric data, and transmit them to the edge computing to determine patient-customized emergency situation. In conclusion, the proposed medical information platform considers the patient's conditions and determine quick emergency situations through big data processing and edge computing, and enables rapid authentication in emergency situations through automatic authentication, and protects patient's information by granting access rights according to the patient situations and the role of the medical staff.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.111-123
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• 1996

In this paper, a new edge-based segmentation algorithm for range image using pseudo reflectance images (PRIs) is proposed. A model of pseudo reflectance which is useful in analyzing three dimensional scene and objects is introduced and then three PRIs are generated by the model. For generating three PRIs, bels and jain's differential window operator is selected and three different light source directions are determined. Three edge images are extracted from each PRI and a fused (logical ORing) edge image is constructed for the benefit of enhanced edge formation. The final segmentation results of the proposed algoritm are obtained after the processing of thinning, labeling and correcting erroeneous regions with the fused edge image. The good performance of edge detection and segmentation is confirmed via computer simulation with synthetic and real range images.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.23-26
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• 1994

A new algorithm using a measure for edge detection from ultrasonic image is proposed. Ultrasonic image is blurred by pre-processing for removing speckle noises and precise edge placement is not clear. Because extracted edge from blurred image is thick, a measure utilizing the absolute difference of mean between two windows is used to thin the thickness of extracted edge in blurred image. The algorithm is effective to process blurred image due to the noise filtering that remove speckle noises. Results of the proposed algorithm using a measure show good edge detection performance comparing with other gradient edge operators.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1025-1028
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• 1999

After detecting the edge which is applying the morphological operators to the hybrid FCNN, we could analyze and compare. The hybrid FCNN is completely removed to the noise in the image, and worked in order to obtain the result image which is closest to the original image. Also, the morphological operator is applied to the image as the method in order to detect more good the edge than the conventional edge. FCNN which is the pipeline type is completely suitable to detecting the image processing as well as the hardware size. In this paper. we would make the structure elements of the morphological operator the variable template and the static template, and compare with the edge enhancement of two images. After being the result which is applying the variable template morphological operator and the static template morphological operator to the image, we could know that the edge images applying the variable template is superior in a edge enhancement side.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.892-894
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• 2013

Edge has been utilized in various application fields with development of technique of digital image processing. In conventional edge detection methods, there are some methods using mask including Sobel, Prewitt, Roberts and Laplacian operator. Those methods are that implement is simple but generates errors of edge detection in images added AWGN(additive white Gaussian noise). Therefore, to compensate the defect of those methods, in this paper, an edge detection algorithm using modified mask is proposed, and it showed superior edge detection property in AWGN.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.1
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• pp.73-85
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• 1998

The purpose of this study was to aid in the use of the digital images by edge-detect interpolation for direct digital periapical images using edge-detect interpolation. This study was performed by image processing of 20 digital periapical images; pixel replication, linear non-interpolation, linear interpolation. and edge-sensitive interpolation. The obtained results were as follows : 1. Pixel replication showed blocking artifact and serious image distortion. 2. Linear interpolation showed smoothing effect on the edge. 3. Edge-sensitive interpolation overcame the smoothing effect on the edge and showed better image.

• ETRI Journal
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• v.27 no.5
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• pp.539-544
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• 2005

An analog CMOS vision chip for edge detection with power consumption below 20mW was designed by adopting electronic switches. An electronic switch separates the edge detection circuit into two parts; one is a logarithmic compression photocircuit, the other is a signal processing circuit for edge detection. The electronic switch controls the connection between the two circuits. When the electronic switch is OFF, it can intercept the current flow through the signal processing circuit and restrict the magnitude of the current flow below several hundred nA. The estimated power consumption of the chip, with $128{\times}128$ pixels, was below 20mW. The vision chip was designed using $0.25{\mu}m$ 1-poly 5-metal standard full custom CMOS process technology.