• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.19-22
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• 2000

In this paper, we present a new multiple description embedded zerotree wavelet coding method using the two splitted thresholds. We first model a half EZW coder and then we present multiple description coder which has two coding channels using wide threshold EZW(WTEZW) coders. To evaluate the performance of the proposed coder, we provide an image coding applications with two descriptions and compare MDC image coding results reported to date.

• 한국지능시스템학회논문지
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• 제13권2호
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• pp.200-208
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• 2003

본 연구에서는 효율적인 학습규칙의 신경망 기반 독립성분분석기법을 이용한 영상신호의 분리와 특징추출을 제안하였다. 제안된 학습규칙은 할선법과 모멘트를 이용한 조합형 고정점 학습알고리즘이다. 여기서 할선법은 독립성분 상호간의 정보를 최소화하기 위한 목적함수의 최적화 과정에서 요구되는 1차 미분에 따른 계산을 간략화하기 위함이고, 모멘트는 최적화 과정에서 발생하는 발진을 억제하여 보다 빠른 학습을 위함이다. 제안된 기법을 $512\times512$의 픽셀을 가지는 10개의 영상을 대상으로 임의의 혼합행렬에 따라 발생되는 혼합영상의 분리에 적용한 결과, 뉴우턴법에 기초한 기존의 알고리즘과 할선법만에 기초한 알고리즘보다 각각 우수한 분리률과 빠른 분리속도가 있음을 확인하였다. 또한 $256\times256$ 픽셀의 10개 지문상과 $480\times225$ 픽셀의 지폐영상에서 선택된 각각 10,000개의 3가지 영상패치들을 대상으로 적용한 결과, 제안된 기법은 뉴우턴법이나 할선법의 알고리즘보다도 빠른 특징추출 속도가 있음을 확인하였다. 한편 추출된 $16\times16$ 펙셀의 160개 독립성분 기저벡터 각각은 영상 각각에 포함된 공간적인 주파수 특성과 방향성을 가지는 경계 특성이 잘 드러나는 국부적인 특징들임을 확인하였다.

• International journal of advanced smart convergence
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• 제13권1호
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• pp.212-220
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• 2024

When a typhoon or natural disaster occurs, a significant number of orchard fruits fall. This has a great impact on the income of farmers. In this paper, we introduce an AI-based method to enhance low-quality raw images. Specifically, we focus on apple images, which are being used as AI training data. In this paper, we utilize both a basic program and an artificial intelligence model to conduct a general image process that determines the number of apples in an apple tree image. Our objective is to evaluate high and low performance based on the close proximity of the result to the actual number. The artificial intelligence models utilized in this study include the Convolutional Neural Network (CNN), VGG16, and RandomForest models, as well as a model utilizing traditional image processing techniques. The study found that 49 red apple fruits out of a total of 87 were identified in the apple tree image, resulting in a 62% hit rate after the general image process. The VGG16 model identified 61, corresponding to 88%, while the RandomForest model identified 32, corresponding to 83%. The CNN model identified 54, resulting in a 95% confirmation rate. Therefore, we aim to select an artificial intelligence model with outstanding performance and use a real-time object separation method employing artificial function and image processing techniques to identify orchard fruits. This application can notably enhance the income and convenience of orchard farmers.

• 대한의용생체공학회:의공학회지
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• 제31권2호
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• pp.134-140
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• 2010

Readily available high resolution brain MRI scans allow detailed visualization of the brain structures. Researchers have focused on developing methods to quantify shape differences specific to diseased scans. We have developed a novel method to quantify shape information for a specific population based on Multidimensional scaling(MDS). MDS is a well known tool in statistics and here we apply this classical tool to quantify shape change. Distance measures are required in MDS which are computed from pair-wise image registrations of the training set. Registration step establishes spatial correspondence among scans so that they can be compared in the same spatial framework. One benefit of our method is that it is quite robust to errors in registrations. Applying our method to 13 brain MRI showed clear separation between normal and diseased (Cushing's syndrome). Intentionally perturbing the image registration results did not significantly affect the separability of two clusters. We have developed a novel method to quantify shape based on MDS, which is robust to image mis-registration.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 춘계학술대회 논문집
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• pp.76-81
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• 2004

Injection molding is the most widely used process fir the industrial forming of plastic articles. During an injection molding process of composites, the fiber-matrix separation and fiber orientation are caused by the flow of molten polymer/fiber mixture. As a result. the product tends to be nonhomogeneous and anisotropic. Hence, it is very important to clarify the relations between separation orientation and injection molding conditions. So far, there is no research on the measurement of fiber orientation using image processing. In this study, the effects of fiber content ratio and molding condition on the fiber orientation-angle distributions are studied experientially. Using the image processing method, the fiber orientation distribution of welding pars in injection-molded products is assessed. And the effects of fiber content and injection mold shapes on the fiber orientation in case of fiber reinforced polymeric composites are studied experimentally.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.778-784
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• 2001

Injection molding is a very important industrial process for the manufacturing of plastics objects. During an injection molding process of composites, the fiber-matrix separation and fiber orientation are caused by the flow of molten polymer/fiber mixture. As a result, the product tends to be nonhomogeneous and anisotropic. Hence, it is very important to clarify the relations between separation orientation and injection molding conditions. So far, there is no research on the measurement of fiber orientation using image processing. In this study, the effects of fiber content ratio and molding condition on the fiber orientation-angle distributions are studied experimentally. Using the image processing method, the fiber orientation distribution of weld-line parts in injection-molded products is assessed. And the effects of fiber content and injection molding conditions on the fiber orientation functions are also discussed.

• 한국공작기계학회논문집
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• 제14권1호
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• pp.73-80
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• 2005

Injection molding is the most widely used process for the industrial forming of plastic articles. During an injection molding process of composites, the fiber-matrix separation and fiber orientation are caused by the flow of molten polymer/fiber mixture. As a result, the product tends to be nonhomogeneous and anisotropic. Hence, it is very important to clarify the relations between separation orientation and injection molding conditions. So far, there is no research on the measurement of fiber orientation using image processing. In this study, the effects of fiber content ratio and molding condition on the fiber orientation-angle distributions are studied experimentally. Using the image processing method, the fiber orientation distribution of welding parts in injection-molded products is assessed. And the effects of fiber content and injection mold shapes on the fiber orientation in case of fiber reinforced polymeric composites are studied experimentally.

• 한국공작기계학회논문집
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• 제15권4호
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• pp.1-7
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• 2006

Injection molding is a very important industrial process for the manufacturing of plastics objects. During an injection molding process of composites, the fiber-matrix separation and fiber orientation are caused by the flow of molten polymer/fiber mixture. As a result, the product tends to be nonhomogeneous and anisotropic. Hence, it is very important to clarify the relations between separation orientation and injection molding conditions. So far, there is no research on the measurement of fiber orientation using image processing. In this study, the effects of fiber content ratio and molding condition on the fiber orientation-angle distributions are studied experimentally. Using the image processing method, the fiber orientation distribution of weld-line in injection-molded products is assessed. And the effects of fiber content and injection mold-gate conditions on the fiber orientation are also discussed.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2000년도 추계학술발표대회 논문집
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• pp.265-270
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• 2000

Injection molding is a very important industrial process for the manufacturing of plastics objects. During an injection molding process of composites, the fiber-matrix separation and fiber orientation are caused by the flow of molten polymer/fiber mixture. As a result, the product tends to be nonhomogeneous and anisotropic. Hence, it is very important to clarify the relations between separation· orientation and injection molding conditions. So far, there is no research on the measurement of fiber orientation using image processing. In this study, the effects of fiber content ratio and molding condition on the fiber orientation-angle distributions are studied experimentally. Using the image processing method, the fiber orientation distribution of weld-line parts in injection-molded products is assessed. And the effects of fiber content and injection molding conditions on the fiber orientation functions are also discussed

• Journal of applied mathematics & informatics
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• 제18권1_2호
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• pp.621-637
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• 2005

A hybrid method solving regularized structured linear total least norm (RSTLN) problems, which have highly ill-conditioned coefficient matrix with special structures, is suggested and analyzed. This scheme combining RSTLN algorithm and separation by parts guarantees the convergence of parameters and has an advantages in reducing the residual norm and relative error of solutions. Computational tests for problems arisen in signal processing and image formation process confirm that the presenting method is effective for more accurate solutions to (R)STLN problem than the (R)STLN algorithm.