• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.1-6
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• 2016

In this paper, we propose an image enhancement method for vehicle recorder by dividing the images into sub-images and finding local histograms of the sub-images. The proposed method includes the following steps. Firstly, the input image is divided into ($N{\times}M$) pieces. And the sub-images are used to make groups using the adjacent piece-images (eg. piece-imagei,j, piece-imagei,j+1, piece-imagei+1,j and piece-imagei+1,j+1). Secondly, the contrast enhancement processes are executed using the local histogram of the sub-images. Finally, overall image is reconstructed by using a transfer function that reflects the characteristics of the sub-image. The proposed method might achieve more enhanced images for vehicle recorder by suppressing excessive image contrast.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.1
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• pp.6-12
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• 2013

Mammography is the most common technique for the early detection of breast cancer. To diagnose correctly and treat of breast cancer efficiently, many image enhancement methods have been developed. This paper presents a nonlinear image enhancement method for the enhancement of digital mammogram. The proposed method is composed of a nonlinear function for brightness improvement and a nonlinear filter for contrast enhancement. The nonlinear function improves the brightness of dark area and extends the dynamic range of bright area, and the nonlinear filter efficiently enhances the specific regions and objects of the mammogram. The final enhanced image was obtained by combining the processed image with the nonlinear function and the filtered image with the nonlinear filter. The proposed nonlinear image enhancement method was confirmed the enhanced performance comparing with other existing methods.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.4
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• pp.209-215
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• 2020

In this paper, we propose an algorithm for segmenting weld bead images using edge enhancement and active contours. In the proposed method, high-frequency filtering and contrast improvement are performed for edge enhancement, and then, by applying the active contour method, only the weld bead region can be obtained. The proposed algorithm detects an edge through high-frequency filtering and reinforces the detected edge by using contrast enhancement. After the edge information is improved in this way, the weld bead area can be extracted by applying the active contour method. The proposed algorithm shows better performance than the existing methods for segmenting the weld bead in the image. For the objective reliability of the proposed algorithm, it was compared with the existing high pass filtering methods, and it was confirmed that the welding bead segmentation of the proposed method is excellent. The proposed method can be usefully used in evaluating the quality of the weld bead through an additional procedure for the segmented weld bead.

• 한국전산유체공학회:학술대회논문집
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• 2004.10a
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• pp.7-14
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• 2004

It is well known that preconditioning methods are efficient for convergence acceleration at compressible low Mach number flows. In this study, the original Euler equations and three preconditioners nondimensionalized differently are implemented in two dimensional inviscid bump flows using the 3rd order MUSCL and DADI schemes as flux discretization and time integration respectively. The multigrid and local time stepping methods are also used to accelerate the convergence. The test case indicates that a properly modified local preconditioning technique involving concepts of a global preconditioning one produces Mach number independent convergence. Besides, an asymptotic analysis for properties of preconditioning methods is added.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.113-116
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• 2001

The conventional K-means algorithm is widely used in vector quantizer design and clustering analysis. Recently modified K-means algorithm has been proposed where the codevector updating step is as fallows: new codevector = current codevector + scale factor (new centroid - current codevector). This algorithm uses a fixed value for the scale factor. In this paper, we propose a new algorithm for the enhancement of learning time in fuzzy c-means a1gorithm. Experimental results show that the proposed method produces codebooks about 5 to 6 times faster than the conventional K-means algorithm with almost the same Performance.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.104-111
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• 2010

This paper presents an adaptive image enhancement method using the spatial frequency property in the DCT(discrete cosine transform) compressed domain. The dc coefficients, the illumination components of image, are adjusted to compress the dynamic range of image, and the ac coefficients are modified to enhance the contrast by using the human visual system(HVS) and the spatial frequency property. The ac coefficients are separated into vertical direction, horizontal direction, and mixed spatial frequency components, and adaptively modified to minimize the block artifacts that possibly occur in the image enhancement. The proposed method using dynamic range compression and adaptive contrast enhancement shows the advanced performance without the block artifact compared with existing method.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.51-60
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• 2024

Aiming at the problem of low contrast and difficult to recognize video images in low-light environment, we propose an adaptive contrast compensation enhancement algorithm based on human visual perception. First of all, the video image characteristic factors in low-light environment are extracted: AL (average luminance), ABWF (average bandwidth factor), and the mathematical model of human visual CRC(contrast resolution compensation) is established according to the difference of the original image's grayscale/chromaticity level, and the proportion of the three primary colors of the true color is compensated by the integral, respectively. Then, when the degree of compensation is lower than the bright vision precisely distinguishable difference, the compensation threshold is set to linearly compensate the bright vision to the full bandwidth. Finally, the automatic optimization model of the compensation ratio coefficient is established by combining the subjective image quality evaluation and the image characteristic factor. The experimental test results show that the video image adaptive enhancement algorithm has good enhancement effect, good real-time performance, can effectively mine the dark vision information, and can be widely used in different scenes.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.4
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• pp.395-401
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• 2001

The characteristics of heat transfer and pressure drop through tubes has been investigated experimentally for a compound heat transfer enhancement. The test tubes were spirally indented tubes with wire coil inserts which had a various combinations of pitch and helix angles. Pure water was used as working fluids for the experiments, Heat transfer coefficients and friction factors of the test tubes were evaluated from the values of measured temperatures, flow rates and pressure drops. An performance evaluation was performed to find an optimal combination of spirally indented tubes with wire coil inserts. When the helix angle of wire coil insert are $71^{\circ}-72^{\circ}$, the best heat transfer enhancement was shown. The friction factor was 9 - 13 times higher than those in smooth tubes, and the heat transfer was enhanced a maximum of 500%.

• Journal of the Korean Society of Industry Convergence
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• v.13 no.1
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• pp.23-30
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• 2010

This paper presents a histogram equalization based on the nonlinear transformation function for enhancing the quality of medical images. The nonlinear transformation function is applied to adaptively equalize the brightness of the image according to its intensity level frequency. The logistic function is used as a nonlinear transformation function, which is calculated by only using the intensity level with maximum frequency and the maximum intensity level in an histogram, and the total number of pixels. The proposed method has been applied for equalizing 8 medical images with a different resolution and histogram distribution. The experimental results show that the proposed method has the superior enhancement performances compared with the conventional histogram equalization. And the proposed histogram equalization can be used in various multimedia systems in real-time.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.217-220
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• 2000

This paper describes the application of a neural network based adaptive line enhancer (ALE) for enhancement of the weak QRS complex corrupted with background noise. Modified fully-connected recurrent neural network is used as a nonlinear adaptive filter in the ALE. The connecting weights between network nodes as well as the parameters of the node activation function are updated at each iteration using the gradient descent algorithm. The real ECG signal buried with moderate and severe background noise is applied to the ALE. Simulation results show that the neural network based ALE performs well the enhancement of the QRS complex from noisy ECG signals.