• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.252-259
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• 2022

Artificial intelligence is used in fusion with image processing techniques using cameras. Image processing technology is a technology that processes objects in an image received from a camera in real time, and is used in various fields such as security monitoring and medical image analysis. If such image processing reduces the accuracy of recognition, providing incorrect information to medical image analysis, security monitoring, etc. may cause serious problems. Therefore, this paper uses a mixture of YOLOv4-tiny model and image processing algorithm and uses the COCO dataset for learning. The image processing algorithm performs five image processing methods such as normalization, Gaussian distribution, Otsu algorithm, equalization, and gradient operation. For RGB images, three image processing methods are performed: equalization, Gaussian blur, and gamma correction proceed. Among the nine algorithms applied in this paper, the Equalization and Gaussian Blur model showed the highest object detection accuracy of 96%, and the gamma correction (RGB environment) model showed the highest object detection rate of 89% outdoors (daytime). The image binarization model showed the highest object detection rate at 89% outdoors (night).

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.495-508
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• 2015

In this paper, a novel robust medical images watermarking scheme is proposed. In traditional methods, the added watermark may alter the host medical image in an irreversible manner and may mask subtle details. Consequently, we propose a method for medical image copyright protection that may remedy this problem by embedding the watermark without modifying the original host image. The proposed method is based on the visual cryptography concept and the dominant blocks of wavelet coefficients. The logic in using the blocks dominants map is that local features, such as contours or edges, are unique to each image. The experimental results show that the proposed method can withstand several image processing attacks such as cropping, filtering, compression, etc.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.380-383
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• 2003

The purpose of this study is to develope prototype EPID system and improve image quality of radiation therapy field imaging system using CCD camera. For this research we used Linac(Clinac 4/100), Copper metal plate, $Gd_2O_2S_2$ phosphor and CCD camera(Photronic). In this study we find best thickness of buil-up metal plate and acquired projection image of humanoid head phantom. Also we enhanced raw image data using superposition and histogram stretching method. Through the thickness optimized of metal plate and image processing, we confirmed of an improved image quality of an EPID system using CCD camera. As result, highest quality image was acquired at 1mm thickness of Copper metal plate and improved image quality by image processing methods.

• Journal of Biomedical Engineering Research
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• v.15 no.1
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• pp.63-70
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• 1994

A medical image workstation was developed using multimedia technique. The system based on PC-486DX was designed to acquire medical images produced by medical imaging instruments and related audio information, that is, doctors'reporting results. Input int'ormation was processed and analyzed, then the results were presented in the form of graph and animation. All the informations of the system were hierarchically related with the image as the apex. Processing and Analysis algorithms were implemented so that the diagnostic accuracy could be improved. The diagnosed id'ormation can be transferred for patient diagnosis through LAN (local area network).

• Proceedings of the Korean Society of Medical Physics Conference
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• 2006.08a
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• pp.152-152
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• 2006

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.658-663
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• 1999

2D sliced CT images hardly express the human disease in a space. This space expression can be reconstructed into 3D image by piling up the CT sliced image in succession. In medical image, in order to get the reconstructed 3D images, expensive system or much calculation time is needed. But by changing the method of reconstruction procedure and limit the range, the reconstruction time could be reduced. In this study, to reduce the processing time and memory, we suggested a method of interpolation and ray casting processing at the same time in a limited range. Such a limited range processing have advantages that we could reduce the unnecessary interpolation and ray casting. Through a experiment, it is founded that the reconstruction time and the memory was much reduced.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.718-721
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• 1988

In this paper, we develop 256*256*8 bit real-time image digitizer with the IBM-PC as a image processor. With this developed system, we process a chest X-ray image, which is a medical image, using the adaptive algorithm. In the future, we consider that the application of this developed system is extended in the various fields.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.475-480
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• 1994

For the effective management of medical images, it becomes popular to use computing machines in medical practice, namely PACS. However, the amount of image data is so large that there is a lack of storage space. We usually use data compression techniques to save storage, but the process speed of machines is not fast enough to meet surgical requirement. So a special hardware system processing medical images faster is more important than ever. To meet the demand for high speed image processing, especially image compression and decompression, we designed and implemented the medical image CODEC (COder/DECoder) based on MISD (Multiple Instruction Single Data stream) architecture to adopt parallelism in it. Considering not being a standard scheme of medical image compression/decompression, the CODEC is designed programable and general. In this paper, we use JPEG (Joint Photographic Experts Group) algorithm to process images and evalutate the CODEC.

• Imaging Science in Dentistry
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• v.45 no.2
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• pp.81-87
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• 2015

Purpose: Contrast, sharpness, enhancement, and density can be changed in digital systems. The important question is to what extent the changes in these variables affect the accuracy of caries detection. Materials and Methods: Forty eight extracted human posterior teeth with healthy or proximal caries surfaces were imaged using a photostimulable phosphor (PSP) sensor. All original images were processed using a six-step method: (1) applying "Sharpening 2" and "Noise Reduction" processing options to the original images; (2) applying the "Magnification 1:3" option to the image obtained in the first step; (3) enhancing the original images by using the "Diagonal/"option; (4) reviewing the changes brought about by the third step of image processing and then, applying "Magnification 1:3"; (5) applying "Sharpening UM" to the original images; and (6) analyzing the changes brought about by the fifth step of image processing, and finally, applying "Magnification 1:3." Three observers evaluated the images. The tooth sections were evaluated histologically as the gold standard. The diagnostic accuracy of the observers was compared using a chi-squared test. Results: The accuracy levels irrespective of the image processing method ranged from weak (18.8%) to intermediate (54.2%), but the highest accuracy was achieved at the sixth image processing step. The overall diagnostic accuracy level showed a statistically significant difference (p=0.0001). Conclusion: This study shows that the application of "Sharpening UM" along with the "Magnification 1:3" processing option improved the diagnostic accuracy and the observer agreement more effectively than the other processing procedures.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.92-95
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• 1994

As computer systems to make medical practice easy are widely used, a special hardware system processing medical data fast becomes more important. To meet the urgent demand for high speed image processing, especially image compression and decompression, we designed and implemented the medical image CODEC (COder/BECoder) based on MISD(Multiple Instruction Single Data stream) architecture to adopt parallelism in it. Considering not being a standart scheme of medical mage compression/decompress ion, the CODEC is designed programable and general. In this paper, we use JPEG (Joint Photographic Experts Group) algorithm to process images fast and evalutate it.