• Restorative Dentistry and Endodontics
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• 제15권1호
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• pp.67-80
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• 1990

This study was performed for elucidating the effects on surface polishing of composite resins. In this study, Silux(microfilled), Graft(hybrid), Bisfil- I (hybrid posterior) and Hi-pol(conventional) were used. Sixty specimens were made with 4 brands of composite resins and Optilux system in $2.0{\times}1.3{\times}1.0cm$ resin block which has a cavity with 0.5cm diameter and 0.5cm depth. Polishing was done with #600 sand paper and Soflex, Super-snap, Micron finishing system, or Composite polishing kit. Final polished surfaces were measured by roughness tester(Kasaka Lab. Ltd., Japan) and image analyser(Omnimet Image Analyser, Buehler, USA). The results were as follows, 1. The celluloid strip produced the smoothest surfaces. 2. Light curing microfilled composite resin, Silux, had smoother surface than any others. 3. The surfaces polished by Soflex were smoothest. 4. Aluminum oxide disk, Soflex and Super-Snap, made smoother surface than diamond bur, M.F.S., or silicon point, Composite polishing kit. 5. The roughness values of surface polished by M.F.S. composed of diamond burs, were less than those of Composite polishing kit made from silicone points.

• 한국정보통신학회논문지
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• 제8권7호
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• pp.1453-1463
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• 2004

기존의 레벨셋을 이용한 이미지 분할 방법은 화소값의 기울기를 이용하기 때문에 지역적 형태에 좌우되는 문제점을 지니고 있다. 본 논문에서는 평활한 구동력을 위하여 레벨 셋 함수와 새로운 보상 평활화 함수를 결합시키는 하이브리드 방법을 이용한 방법이 소개된다. 대부분의 경우에 3 교점을 가지고 있지 않다는 가정하에 보상함수를 얻는 방법을 대안으로 고려하였다. 보상함수의 주요 역할은 원보상 함수와 평균 보상함수의 차가 새로운 레벨셋 함수의 합리적인 구동력으로 소개될 수 있다. 본 논문에서 제안한 하이브리드 방법은 기존 레벨셋을 이용한 방법의 단점을 최소화시키는 방법이다.

• 한국정보통신학회논문지
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• 제14권12호
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• pp.2622-2627
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• 2010

24시간 무인 감시 시스템에서 정확한 얼굴 인식은 절대적으로 필요한 요소이다. 그러나 얼굴 인식은 얼굴 영상의 왜곡, 조명, 얼굴의 크기, 얼굴 표정, 배경 영상 등의 변화로 인해 많은 제약이 있다. 본 연구에서는 얼굴 인식의 성능 향상을 위하여 혼합형 신경회로망을 제안한다. 제안한 방식은 신경회로망의 비지도학습 방식인 SOM과 LVQ 알고리즘을 이용하여 구성한다. 제안한 방식의 유용성을 확인하기 위하여 고유얼굴 방식, 은닉 마코프 모델 방식, 다층 신경회로망 방식과 비교한다.

• 센서학회지
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• 제24권6호
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• pp.359-363
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• 2015

This paper proposes an algorithm that reduces the conversion time of a single-slope A/D converter (SSADC) that has n-bit resolution, which typically is limited by conversion time taking up to $2^n$ clock cycles for an operation. To improve this situation, we have researched a novel hybrid-type A/D converter that consists of a pseudo-pipeline A/D converter and a conventional SSADC. The pseudo-pipeline A/D converter, using a single-stage of analog components, determines the most significant bits (MSBs) or upper bits and the conventional SSADC determines the remaining bits. Therefore, the modified SSADC, similar to the hybrid-type A/D converter, is able to significantly reduce the conversion time because the pseudo-pipeline A/D converter, which determines the MSBs (or upper bits), does not rely on a clock. The proposed A/D converter was designed using a $0.35-{\mu}m$ 2-poly 4-metal standard complementary metal oxide semiconductor (CMOS) technology process; additionally, its characteristics were simulated.

• Current Optics and Photonics
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• 제2권6호
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• pp.540-546
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• 2018

We propose an implementation scheme for an optical encryption system with hybrid-pattern random keys. In the encryption process, a pair of random phase keys composed of a white-noise phase key and a structured phase key are positioned in the input plane and Fourier-spectrum plane respectively. The output image is recoverable by digital reconstruction, using the conjugate of the encryption key in the Fourier-spectrum plane. We discuss the system encryption performance when different combinations of phase-key pairs are used. To measure the effectiveness of the proposed method, we calculate the statistical indicators between original and encrypted images. The results are compared to those generated from a classical double random phase encoding. Computer simulations are presented to show the validity of the method.

• 복식문화연구
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• 제31권4호
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• pp.467-488
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• 2023

The purpose of this study is to determine the concepts of heterotopic image and fashion space, and the characteristics of fashion space and images from the perspective of fashion brands and users. This study examines the evolution of fashion space and consumers with it, based on Foucault's theory of heterotopia, which refers to spaces that blend contradictory features not typically found within a single physical structure. This is accomplished by employing a single case study of Ader Error's Ader Space, a Seoul-based brand known for its unique approach to presenting and communicating fashion. Based on an analysis of Instagram posts of Ader Error along with the hashtag searches "aderspace" and "adererror", this study categorizes heterotopia from the perspective of fashion brands into three properties: fashion space as a medium for selling fashion products; fashion space as getaway to hybrid fashion practices; and fashion space as an illusionary place to experience fashion. From the user perspective, the heterotopic image of Ader Space portrayed on Instagram is characterized by the image of fashion products in an extraordinary fashion space, the image of a fashion space beyond space and time, and the image of exposing the hidden and the illusion-compensation of fashion space. This study contributes to a heightened understanding of the evolutionary concept of the fashion space.

• Korean Journal of Radiology
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• 제23권4호
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• pp.402-412
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• 2022

Objective: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images. Materials and Methods: This retrospective study included 123 patients (mean age ± standard deviation, 63 ± 11 years; male:female, 70:53) who underwent contrast-enhanced abdominopelvic LDCT between May and August 2020 and had prior SDCT obtained using the same CT scanner within a year. LDCT images were reconstructed with hybrid iterative reconstruction (h-IR) and DLIR at medium and high strengths (DLIR-M and DLIR-H), while SDCT images were reconstructed with h-IR. For quantitative image quality analysis, image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured in the liver, muscle, and aorta. Among the three different LDCT reconstruction algorithms, the one showing the smallest difference in quantitative parameters from those of SDCT images was selected for qualitative image quality analysis and lesion detectability evaluation. For qualitative analysis, overall image quality, image noise, image sharpness, image texture, and lesion conspicuity were graded using a 5-point scale by two radiologists. Observer performance in focal liver lesion detection was evaluated by comparing the jackknife free-response receiver operating characteristic figures-of-merit (FOM). Results: LDCT (35.1% dose reduction compared with SDCT) images obtained using DLIR-M showed similar quantitative measures to those of SDCT with h-IR images. All qualitative parameters of LDCT with DLIR-M images but image texture were similar to or significantly better than those of SDCT with h-IR images. The lesion detectability on LDCT with DLIR-M images was not significantly different from that of SDCT with h-IR images (reader-averaged FOM, 0.887 vs. 0.874, respectively; p = 0.581). Conclusion: Overall image quality and detectability of focal liver lesions is preserved in contrast-enhanced abdominopelvic LDCT obtained with DLIR-M relative to those in SDCT with h-IR.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권2호
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• pp.102-110
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• 2015

The main source of noise in computed tomography (CT) images is a quantum noise, which results from statistical fluctuations of X-ray quanta reaching the detector. This paper proposes a neural network (NN) based hybrid filter for removing quantum noise. The proposed filter consists of bilateral filters (BFs), a single or multiple neural edge enhancer(s) (NEE), and a neural filter (NF) to combine them. The BFs take into account the difference in value from the neighbors, to preserve edges while smoothing. The NEE is used to clearly enhance the desired edges from noisy images. The NF acts like a fusion operator, and attempts to construct an enhanced output image. Several measurements are used to evaluate the image quality, like the root mean square error (RMSE), the improvement in signal to noise ratio (ISNR), the standard deviation ratio (MSR), and the contrast to noise ratio (CNR). Also, the modulation transfer function (MTF) is used as a means of determining how well the edge structure is preserved. In terms of all those measurements and means, the proposed filter shows better performance than the guided filter, and the nonlocal means (NLM) filter. In addition, there is no severe restriction to select the number of inputs for the fusion operator differently from the neuro-fuzzy system. Therefore, without concerning too much about the filter selection for fusion, one could apply the proposed hybrid filter to various images with different modalities, once the corresponding noise characteristics are explored.

• 한국지역지리학회지
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• 제12권4호
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• pp.496-507
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• 2006

본 연구는 고해상도 자료와 하이퍼스펙트럴 자료를 혼용하여 하와이 화산 국립공원 내 해안 지역의 식생을 분류하고자 하였다. 연구지역에 주로 나타나는 식생은 3종의 초본(broomsedge, natal redtop, and pili)과 작은 관목 등으로 대표되는 비초본으로 구분된다. 분류 기법으로는 unsupervised classification과 supervised classification을 결합한 하이브리드법을 이용하여 전체적으로 3단계 분류과정을 적용하였다. 첫째로는, IKONOS 고해상 위성자료를 이용하여, 식생 및 비식생지역을 unsupervised classification법을 통해 분류하였다. 두 번째로는, minimum noise fraction(MNF) transformation을 이용하여 AVIRIS하이퍼스펙트럴 자료로부터 주성분을 추출하여 자료를 압축하는 과정을 거쳤다. 20미터 해상도를 가진 AVIRIS 픽셀들은 대부분 용암면과 식생면으로부터 반사된 복사신호가 혼합되어 있기때문에, 용암과 식생의 지표피복 비율에 따른 선형모형을 적용하여 용암면이 갖는 반사 신호를 각 픽셀로부터 제거하였다. 최종적으로, 각 픽셀에 대하여, 식생피복 비율에 비례하는 AVIRIS 하이퍼스펙트럴 자료의 식생성분을 토대로 maximum likelihood algorithm에 따라 supervised classification법을 적용하여 초지 및 관목으로 대표되는 지표식생을 분류하였다.

• International Journal of Knowledge Content Development & Technology
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• 제5권2호
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• pp.11-24
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• 2015

It is common for archive libraries to provide public access to historical and ancient document image collections. It is common for such document images to require specialized processing in order to remove background noise and become more legible. Document images may be contaminated with noise during transmission, scanning or conversion to digital form. We can categorize noises by identifying their features and can search for similar patterns in a document image to choose appropriate methods for their removal. In this paper, we propose a hybrid binarization approach for improving the quality of old documents using a combination of global and local thresholding. This article also reviews noises that might appear in scanned document images and discusses some noise removal methods.