• 한국통신학회논문지
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• 제34권7C호
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• pp.649-653
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• 2009

디지털 영상은 영상압축이나 기타 다양한 디지털 처리에 용이한 장점이 있는 반면 위/변조가 상대적으로 용이하기 때문에 그에 대한 대응을 위한 다양한 디지털 워터마킹 기법이 개발되었다. 워터마킹 기법은 공간 또는 주파수 영역에서의 다양한 적용에 가능한데, 본 연구에서는 디지털 콘텐츠 대부분이 압축되어 전송, 저장되는 추세와, 최근 대부분의 멀티미디어 동영상 코덱 표준으로 채택이 되고 있는 H.264/AVC 언코더를 기반으로 한 워터마크 삽입을 실시간으로 수행하기 위한 기법을 제시한다.

• 한국통신학회논문지
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• 제10권2호
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• pp.93-103
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• 1985

대역폭 압축에 의한 디지털 신호처리 기술은 최근 몇 년동안 집적회로 기술의 발달에 따라 급성장해왔다. 본 연구에서는 화면의 중앙에 시야가 돋보이며 눈의 감각과 일치하는 Hadamard Matrix의 중앙에 Weight를 준 Nonorthogonal 변환인 Weighted Handamard Matrix를 구하여 실시간처리를 위한 고속계산방법과 Hardware system을 연구하였다. 따라서 본 연구는 항공사진, X-Ray, CATV, 인공위성통신 등 디지탈영상신호처리에 사용할 수 있을 것이다.

• 대한의생명과학회지
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• 제29권2호
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• pp.53-57
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• 2023

The main objective of pathologists is to achieve accurate lesion diagnoses, which has become increasingly challenging due to the growing number of pathological slides that need to be examined. However, using digital technology has made it easier to complete this task compared to older methods. Digital pathology is a specialized field that manages data from digitized specimen slides, utilizing image processing technology to automate and improve analysis. It aims to enhance the precision, reproducibility, and standardization of pathology-based researches, preclinical, and clinical trials through the sophisticated techniques it employs. The advent of whole slide imaging (WSI) technology is revolutionizing the pathology field by replacing glass slides as the primary method of pathology evaluation. Image processing technology that utilizes WSI is being implemented to automate and enhance analysis. Artificial intelligence (AI) algorithms are being developed to assist pathologic diagnosis and detection and segmentation of specific objects. Application of AI-based digital pathology in biomedical researches is classified into four areas: diagnosis and rapid peer review, quantification, prognosis prediction, and education. AI-based digital pathology can result in a higher accuracy rate for lesion diagnosis than using either a pathologist or AI alone. Combining AI with pathologists can enhance and standardize pathology-based investigations, reducing the time and cost required for pathologists to screen tissue slides for abnormalities. And AI-based digital pathology can identify and quantify structures in tissues. Lastly, it can help predict and monitor disease progression and response to therapy, contributing to personalized medicine.

• 소성∙가공
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• 제7권6호
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• pp.575-585
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• 1998

An automated surface-strain measuring system using the image processing technique is developed in the present study which consists of the hardware to capture and to display digital images. and the software to calculate the 3-D informations of grid points from two views. New or improved algorithms for the mapping and establishing correspondence of grid points and elements the camera calibration and the subpixel measurement of grid points are implemented. As an application of the present system the surface-strains of deformed blanks in the limitting dome height test the square cup deep-drawing and punch stretching to obtain the forming limit diagram are measured. The results are com-pared with those obtained by conventional manual methods.

• 인터넷정보학회논문지
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• 제4권4호
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• pp.27-34
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• 2003

오늘날, 디지털 이미지 도구 프로그램은 전문가가 아니더라도 누구나 개인용 컴퓨터를 이용하여 쉽고 빠르게 영상을 조작하여 사용할 수 있게 되었다. 그 결과 디지털 컨텐츠의 저작권 보호 및 변조된 영상의 무결성을 보증하는 것이 주요 문제가 되고있다. 본 논문에서는 워터마크 정보는 물론 조작된 영상의 위치까지 검출할 수 있는 하이브리드 워터마킹 알고리즘을 설계하였다. 이를 위해 이산 웨이블릿 변환을 이용하여 영상의 저주파 대역에 PN-시권스를 워터마크로 삽입하였고, 원영상 없이도 검출이 가능하게 하였다. 워터마크 신호를 파괴하기 위한 다양한 공격의 실험 결과 제안한 알고리즘은 강인성을 나타내었고 추출 후 변조된 영상의 위치도 확인할 수 있었다.

• 한국응용곤충학회지
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• 제42권1호
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• pp.57-63
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• 2003

해충의 발생시기와 발생량에 대한 정확한 예찰정보는 해충의 효율적인 종합적 방제를 위하여 필수적으로 요구된다. 해충의 효율적인 발생 예찰조사를 위해 디지털 영상처리 알고리즘을 이용하여 벼농경지에서 주요 해충인 멸구류를 자동적으로 인식하고 밀도를 측정하도록 하였다. 야외경작지에서 촬영한 입력영상에 대해 구성인자분해과정, 탑헷(top-hat)변환, 역치적용, 최소/최대 필터링 등의 방법을 적용하여 벼 잎에 붙어 있는 멸구 개체를 인식하고 개체수를 헤아렸다. 평균인식율은 95.8%를 보였다. 또한 인지된 각 멸구류 개체 크기를 측정하여 멸구류의 연령분포 추정을 가능하게 하였다

• 한국레이저가공학회지
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• 제12권1호
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• pp.19-24
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• 2009

Because of its fast and precise welding performance, laser welding is becoming a new excellent welding method. However, the precise focusing and robust seam tracking are required to apply laser welding to the practical fields. In order to laser weld a type of T joint like a circular pipe on a square pipe, which could be met in the three dimensional structure such as an aluminum space frame, a visual sensor system was developed for automation of focusing and seam tracking. The developed sensor system consists of a digital CCD camera, a structured laser, and a vision processor. It is moved and positioned by a 2-axis motorized stage, which is attached to a 6 axis robot manipulator with a laser welding head. After stripe-type structured laser illuminates a target surface, images are captured through the digital CCD camera. From the image, seam error and defocusing error are calculated using image processing algorithms which includes efficient techniques handling continuously changed image patterns. These errors are corrected by the stage off-line during welding or teaching. Laser welding of a circular pipe on a square pipe was successful with the vision tracking system by reducing the path positioning and de focusing errors due to the robot teaching or a geometrical variation of specimens and jig holding.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1989년도 춘계학술대회
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• pp.23-26
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• 1989

This paper describes the automatic recognition technique for heart enlargement diagnosis with the chest X-ray films enhanced by digital image processing. The technique measures a maximum transverse of the daiphragm and a maximum transverse of the heart by means of direction signature algorithms, then calculates the desired ratio of these two measured values. This is often refered to a cadiothoracic ratio which gives as useful clue for heart enlargement symptom. The experiment results in this paper show presented method is more efficient than the manual diagnosis method of the symptom.

• 디지털산업정보학회논문지
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• 제10권3호
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• pp.237-247
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• 2014

This paper describes a 2D discrete-time wavelet transform for which the Q-factor is easily specified. Hence, the transform can be tuned according to the oscillatory behavior of the image signal to which it is applied. The tunable Q-factor wavelet transform (TQWT) is a fully-discrete wavelet transform for which the Q-factor, Q, of the underlying wavelet and the asymptotic redundancy (over-sampling rate), r, of the transform are easily and independently specified. In particular, the specified parameters Q and r can be real-valued. Therefore, by tuning Q, the oscillatory behavior of the wavelet can be chosen to match the oscillatory behavior of the signal of interest, so as to enhance the sparsity of a sparse signal representation. The TQWT is well suited to fast algorithms for sparsity-based inverse problems because it is a Parseval frame, easily invertible, and can be efficiently implemented. The TQWT can also be used as an easily-invertible discrete approximation of the continuous wavelet transform. The transform is based on a real valued scaling factor (dilation-factor) and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. The transform is parameterized by its Q-factor and its oversampling rate (redundancy), with modest oversampling rates (e. g. 3-4 times overcomplete) being sufficient for the analysis/synthesis functions to be well localized. Therefore, This method services good performance in image processing fields.

• 반도체디스플레이기술학회지
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• 제20권2호
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• pp.126-130
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• 2021

The ball grid array is one of the packaging methods that used in high density printed circuit board. Solder void defects caused by voids in the solder ball during the BGA process do not directly affect the reliability of the product, but it may accelerate the aging of the device on the PCB layer or interface surface depending on its size or location. Void inspection is important because it is related in yields with products. The most important process in the optical inspection of solder void is the segmentation process of solder and void. However, there are several segmentation algorithms for the vision inspection, it is impossible to inspect all of images ideally. When X-Ray images with poor contrast and high level of noise become difficult to perform image processing for vision inspection in terms of software programming. This paper suggests the solution to deal with the suggested problem by means of using Mask R-CNN instead of digital image processing algorithm. Mask R-CNN model can be trained with images pre-processed to increase contrast or alleviate noises. With this process, it provides more efficient system about complex object segmentation than conventional system.