• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.8B
• /
• pp.1400-1412
• /
• 2000

In this paper, we propose a technique for image enhancement, especially for denoising and deblocking based on wavelets. In this proposed algorithm, frame wavelet system designed as a optimal edge detector was used. And our theory depends on Lipschitz regularity, spatial correlation, and some important assumptions. The performance of the proposed algorithm was compared with three popular test images in image processing area. Experimental results show that the performance of the proposed algorithm was better than other previous denoising techniques like spatial averaging filter, Gaussian filter, median filter, Wiener filter, and some other wavelet based filters in the aspect of both PSNR and human visual system, The experimental results also show approximately the same capability of deblocking as the previous developed techniques

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.50 no.9
• /
• pp.431-437
• /
• 2001

Since the eddy current problem usually depends on the geometry of the moving conductive sheet and the shape of the pole projection area, there is no general method to find out its analytical solution. The analysis of the eddy current in a rotating disk is performed in the case of time-invariant field to find its analytical solution. As a method to solve the eddy current problem, the concept of the Coulomb charge and image method are proposed with the consideration of the boundary condition. Firstly, the line charge is obtained from the volume charge generated in the rotating disk and Coulomb's law is applied. Secondly, the finite disk radius is considered by introducing an imaginary eddy current to satisfy the boundary condition that the radial component of the eddy current is zero at the edge of the relating disk. Thirdly, the braking torque is calculated by applying Lorentz force law. Finally, the computed braking torque is compared with the measured one As a result, it can be said that the proposed model presents fairly accurate results in a low angular velocity range although a large error is observed as the angular velocity of the disk increases.

• Journal of IKEEE
• /
• v.7 no.2 s.13
• /
• pp.271-280
• /
• 2003

This paper presents an effective method to segment objects from the ultrasound medical image which is inherently corrupted by speckle noise. In order to reduce the speckle noise morphological opening was used as preprocessing. For the preprocessed image, sample variance of neighborhood pixels is to be computed to classify where the pixel is located on the edge region or homogeneous region. Then pseudomedian filtering with different window size is taken according to the region classified, named adaptive pseudomedian filter. Various experimental results were presented to prove superiority of the proposed filter.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.2
• /
• pp.283-290
• /
• 2006

The cellular neural networks have the structure that consists of an array of the same cell which is a simple processing element, and each of the cells has local connectivity and space invariant template properties. So, it has a very suitable structure for the hardware implementation. But, it is impossible to have a one-to-one mapping between the CNN hardware processors and the pixels of the practical large image. In this paper, a $5{\times}5$ CNN hardware processor with pipeline input and output that can be applied to the time-multiplexing processing scheme, which processes the large image with a small CNN cell block, is designed. the operation of the implemented $5{\times}5$ CNN hardware processor is verified from the edge detection and the shadow detection experimentations.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1240-1242
• /
• 1996

In a still mill, the effective surface defect inspection algorithm is necessary. For this purpose, this paper proposed the preprocessing algorithm for surface defect inspection of cold mill strip. This consists of live steps. They are edge detection, binarizing, noise deletion, combining of fragmented defect and selecting the largest defect. Especially, binarizing is a critical problem. Bemuse the performance of the preprocessing is largely depend on the binarized image. So, we develope the adaptive thresholding method, which is multilevel thresholding. The thresholding value is varied according to the mean graylevel value of each test image. To investigate the performance of the proposed algorithm, we classified the detected defect using neural network. The test image is 20 defect images captured at German Sick Co. This algorithm is proved to have good property in cold mill strip surface inspection.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.3
• /
• pp.366-370
• /
• 2010

This paper presents an automatic Oriental ink-rendering technique that recreates the artistic style of Oriental paintings from a single image. In Oriental paintings are characterized by strokes with various thickness and disordered dispersion. In this study, a stroke drawing method was developed based on the canny edge detector and radial curvature that are suitable for lines with varied thickness even along a single stroke. A dispersion-shading method was likewise developed by applying a set of iterated dual-filtering, and intensity exaggeration methods. The dispersion-shading method is designed to increase the local shade details, to decrease the global shade. Unlike the existing watercolor-rendering and abstraction system the proposed dispersion-shading method achieves disordered shade details rather than simplification.

• Nuclear Engineering and Technology
• /
• v.50 no.3
• /
• pp.368-378
• /
• 2018

Understanding of turbulent flow in the reactor coolant pump (RCP) is a premise of the optimal design of the RCP. Flow structures in the RCP, in view of the specially devised spherical casing, are more complicated than those associated with conventional pumps. Hitherto, knowledge of the flow characteristics of the RCP has been far from sufficient. Research into the nonintrusive measurement of the internal flow of the RCP has rarely been reported. In the present study, flow measurement using particle image velocimetry is implemented to reveal flow features of the RCP model. Velocity and vorticity distributions in the diffuser and spherical casing are obtained. The results illuminate the complexity of the flows in the RCP. Near the lower end of the discharge nozzle, three-dimensional swirling flows and flow separation are evident. In the diffuser, the imparity of the velocity profile with respect to different axial cross sections is verified, and the velocity increases gradually from the shroud to the hub. In the casing, velocity distribution is nonuniform over the circumferential direction. Vortices shed consistently from the diffuser blade trailing edge. The experimental results lend sound support for the optimal design of the RCP and provide validation of relevant numerical algorithms.

• Current Optics and Photonics
• /
• v.2 no.2
• /
• pp.153-164
• /
• 2018

In semiconductor manufacturing, critical dimensions indicate the features of patterns formed by the semiconductor process. The purpose of measuring critical dimensions is to confirm whether patterns are made as intended. The deposition process for an organic light emitting diode (OLED) forms a luminous organic layer on the thin-film transistor electrode. The position of this organic layer greatly affects the luminescent performance of an OLED. Thus, a system for measuring the position of the organic layer from outside of the vacuum chamber in real-time is desired for monitoring the deposition process. Typically, imaging from large stand-off distances results in low spatial resolution because of diffraction blur, and it is difficult to attain an adequate industrial-level measurement. The proposed method offers a new superresolution single-image using a conversion formula between two different optical systems obtained by a deep learning technique. This formula converts an image measured at long distance and with low-resolution optics into one image as if it were measured with high-resolution optics. The performance of this method is evaluated with various samples in terms of spatial resolution and measurement performance.

• Journal of Surface Science and Engineering
• /
• v.54 no.5
• /
• pp.278-284
• /
• 2021

Corrosion of steel plate is common phenomenon which results in the gradual destruction caused by a wide variety of environments. Corrosion monitoring is the tracking of the degradation progress for a long period of time. Corrosion on steel plate appears as a discoloration and any irregularities on the surface. In this study, we developed a quantitative evaluation method of the rust formed on steel plate by using k-means clustering from the corroded area in a given image. The k-means clustering for automated corrosion detection was based on the GrabCut segmentation and Gaussian mixture model(GMM). Image color of the corroded surface at cut-edge area was analyzed quantitatively based on HSV(Hue, Saturation, Value) color space.

• Journal of Korea Multimedia Society
• /
• v.25 no.5
• /
• pp.661-669
• /
• 2022

The purpose of this study is to compare and analyze Deep Learning (DL) and Digital Image Processing (DIP) techniques using the results of the glottis segmentation of the two methods followed by the quantification of the asymmetric degree of the vocal cord mucosa. The data consists of 40 normal and abnormal images. The DL model is based on Deeplab V3 architecture, and the Canny edge detector algorithm and morphological operations are used for the DIP technique. According to the segmentation results, the average accuracy of the DL model and the DIP was 97.5% and 94.7% respectively. The quantification results showed high correlation coefficients for both the DL experiment (r=0.8512, p<0.0001) and the DIP experiment (r=0.7784, p<0.0001). In the conclusion, the DL model showed relatively higher segmentation accuracy than the DIP. In this paper, we propose the clinical applicability of this technique applying the segmentation and asymmetric quantification algorithm to the glottal area in the laryngoscopic images.