• IEIE Transactions on Smart Processing and Computing
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• 제1권1호
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• pp.8-16
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• 2012

An image obtained from a low light environment results in a low-exposure problem caused by non-ideal camera settings, i.e. aperture size and shutter speed. Of particular note, the multiple color-filter aperture (MCA) system inherently suffers from low-exposure problems and performance degradation in its image classification and registration processes due to its finite size of the apertures. In this context, this paper presents a novel method for the color enhancement of low-exposure images and its application to color shift model-based MCA system for image refocusing. Although various histogram equalization (HE) approaches have been proposed, they tend to distort the color information of the processed image due to the range limits of the histogram. The proposed color enhancement algorithm enhances the global brightness by analyzing the basic cause of the low-exposure phenomenon, and then compensates for the contrast degradation artifacts by using an adaptive histogram specification. We also apply the proposed algorithm to the preprocessing step of the refocusing technique in the MCA system to enhance the color image. The experimental results confirm that the proposed method can enhance the contrast of any low-exposure color image acquired by a conventional camera, and is suitable for commercial low-cost, high-quality imaging devices, such as consumer-grade camcorders, real-time 3D reconstruction systems, digital, and computational cameras.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권9호
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• pp.3286-3301
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• 2014

Jung and Yoo proposed the first image interpolation-based reversible data hiding algorithm. Although their algorithm achieved superior interpolation results, the embedding capacity was insufficient. Lee and Huang proposed an improved algorithm to enhance the embedding capacity and the interpolation results. However, these algorithms present limitations to magnify the original image to any resolution and pixels in the boundary region of the magnified image are poorly manipulated. Furthermore, the capacity and the image quality can be improved further. This study modifies the pixel mapping scheme and adopts a bilinear interpolation to solve boundary artifacts. The modified reference pixel determination and an optimal pixel adjustment process can effectively enhance the embedding capacity and the image quality. The experimental results show our proposed algorithm achieves a higher embedding capacity under acceptable visual distortions, and can be applied to a magnified image at any resolution. Our proposed technique is feasible in reversible data hiding.

• 간호행정학회지
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• 제10권2호
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• pp.219-231
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• 2004

Purpose: This study was designed to identify the relationship between image of nursing and satisfaction with clinical practice of nursing students Method: A descriptive research design that examined relationship between image of nurse and satisfaction with clinical practice of nursing students was used for this study, All 350 subjects were obtained by convenience sampling from three nursing diploma programs. The data were collected using an self-reporting questionnaire from May 1st to 31st, 2003. Collected data were analysed on SPSS Win 11.0. Result: There is a significant relationship between image of nurse and satisfaction with clinical practice of nursing student. Classical image of nurse, older age, and satisfaction with nursing of nursing students were identified as the factors that influence significantly on their satisfaction with clinical practice. Conclusions: Nursing student is given a chance to prepare themselves be a nurse through well-structured clinical nursing practice. Therefore, it's important to enhance nursing students' image of nurse and satisfaction with nursing in order to enhance their satisfaction with clinical practice.

• 디자인학연구
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• 제16권4호
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• pp.207-214
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• 2003

수사법이 영상이미지를 구성하는데 중요하게 작용하는 이유는 영상이 비언어적 수단들로 소통되기 때문이다. 영상이미지에 내재된 수사법은 일차적으로는 이야기가 설득력을 갖도록 기능한다. 이차적으로 수사법은 영상을 아름답게 꾸미는 기능을 맡는다. 이로 인해 아름다운 비유법이나 신선한 수사법이 가미된 영상이미지를 접할 때 우리는 좀 더 즐거움과 기쁨을 느끼게 되는 것이다. 한편으로 헐리우드 영화에 의한 볼거리 영상과 디지털 영상 성을 강화시키는 컴퓨터에 의한 가상성의 극대화는 수사적 표현이 또 다른 차원으로 전개되고 있음을 보여주고 있다. 고전적인 서사구조와 달리 현대의 영상은 많은 기표 요소들로 기의를 구축하고 있으며, 각 기표들이 의미작용을 일으키기 위해 은유적으로 구성되고 있는 양상을 갖는다. 본 연구에서는 영상의 의미작용의 요체로서 수사법이 어떻게 작용하고 있는지를 규명하고, 효과적인 영상이미지를 구현하기 위해 수사법을 이해하도록 한다.

• 한국가시화정보학회지
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• 제13권3호
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• pp.15-19
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• 2015

We developed a high-throughput microscopy (HTM) method which enabled us to replace a conventional phase contrast microscopy (PCM) method that has been used as a standard analytical method for airborne asbestos. We could obtain the concentration of airborne asbestos fibers under detection limit by automated image processing and analysis using HTM method. Here we propose an improved image processing algorithm with variable parameters to enhance the accuracy of the HTM analysis. Since the variable parameters that compensate the difference of the brightness are applied to the individual images in our new image processing method, it is possible to enhance the accuracy of the automatic image analysis method for sample slides with low asbestos concentration that caused errors in binary image processing. We demonstrated that enumeration of fibers by improved image processing algorithm remarkably enhanced the accuracy of HTM analysis in comparison with PCM. The improved HTM method can be a potential alternative to conventional PCM.

• Journal of Electrical Engineering and Technology
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• 제7권2호
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• pp.264-272
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• 2012

In the field of medical diagnostics, interested parties have resorted increasingly to medical imaging. It is well established that the accuracy and completeness of diagnosis are initially connected with the image quality, but the quality of the image is itself dependent on a number of factors including primarily the processing that an image must undergo to enhance its quality. This paper introduces an algorithm for medical image compression based on the quincunx wavelets coupled with SPIHT coding algorithm, of which we applied the lattice structure to improve the wavelet transform shortcomings. In order to enhance the compression by our algorithm, we have compared the results obtained with those of other methods containing wavelet transforms. For this reason, we evaluated two parameters known for their calculation speed. The first parameter is the PSNR; the second is MSSIM (structural similarity) to measure the quality of compressed image. The results are very satisfactory regarding compression ratio, and the computation time and quality of the compressed image compared to those of traditional methods.

• 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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• 제10권3호
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• pp.331-342
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• 1989

This paper presents a new algorithm that extracts lung region in X-Rays and enhance.j the region. Comparing to prior algorithms that enhance whole X-Ray image, this algorithm leads more effective results. For this algorithm extracts lung region first, and enhances the lung region excluding parameters of other region. For choosing optimal threshold, we compare OTSU's mothod with the proposed method. We obtain lung boundary using contour following algorithm and Rray level searching method in gray level rescaled image. We Process histogram equalization in lung region and obtain enhanced lung image. By using the proposed algorithm, we obtain lung region effectively in chest X-Ray that need in medical image diagnostic system.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.118-126
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• 2020

In this paper, we present an effective single image fog removal by using the Joint Bright and Dark Channel (JBDC) and pixel-based transmission estimation to enhance the visibility of outdoor images susceptible to degradation due to weather and environmental conditions. The conventional methods include refinement process of coarse transmission with heavy computational complexity. The proposed transmission estimation reveals excellent edge-preserving performance and does not require the refinement process. We estimate the atmospheric light in pixel-based fashion, which can improve the transmission estimation performance and visual quality of the restored image. Moreover, we propose an adaptive transmission estimation to enhance the visual quality specifically in sky regions. Comprehensive experiments on various fog images show that the proposed method exhibits reduced computational complexity and excellent fog removal performance, compared with the existing methods; thus, it can be applied to various fields including real-time devices.

• 한국가구학회지
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• 제12권1호
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• pp.27-37
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• 2001

Automation of wood processing is strongly required to improve the productivity and quality of wood products in wood industry which is one of the most labor-intensive industries. Classification of surface defects on wood boards such as knots is one of the important steps towards a completely automated wood processing system. In this study the possibility of detection of knots by image processing technique was investigated. Algorithm for the automatic determination of threshold value was developed to enhance the flexibility of image processing system. Two different approaches, grid method and tile method, were developed to enhance the speed in extracting features from images. Grid method showed slightly higher processing speed and tile method proved much more stable in determining threshold values. Tile size of $5{\times}5$ pixels or $6{\times}6$ pixels was found to be proper to get stable results with resonable processing time.