• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.6
• /
• pp.295-302
• /
• 2004

On the field of speech processing the treatment of noise is still important problems for speech research. Especially, it has been noticed that the background noise causes remarkable reduction of speech recognition ratio. As the examples of the background noise, there are such various non-stationary noises existing in the real environment as driving noise of automobiles on the road or typing noise of printer. The treatment for these kinds of noises is not so simple as could be eliminated by the former Wiener filter, but needs more skillful techniques. In this paper as one of these trials, we show an algorithm which is a speech enhancement method using a model of mutual inhibition for noise reduction in speech which is contaminated by white noise or background noise mentioned above. It is confirmed that the proposed algorithm is effective for the speech degraded not only by white noise but also by colored noise, judging from the spectral distortion measurement.

• Journal of the Institute of Convergence Signal Processing
• /
• v.15 no.2
• /
• pp.24-29
• /
• 2014

Digital mammography is the most common technique for the early detection of breast cancer. To diagnose the breast cancer in early stages and treat efficiently, many image enhancement methods have been developed. This paper presents a multi-scale contrast enhancement method in the Laplacian pyramid for the digital mammogram. The proposed method decomposes the image into the contrast measures by the Gaussian and Laplacian pyramid, and the pyramid coefficients of decomposed multi-resolution image are defined as the frequency limited local contrast measures by the ratio of high frequency components and low frequency components. The decomposed pyramid coefficients are modified by the contrast measure for enhancing the contrast, and the final enhanced image is obtained by the composition process of the pyramid using the modified coefficients. The proposed method is compared with other existing methods, and demonstrated to have quantitatively good performance in the contrast measure algorithm.

• Journal of Korean Academy of Nursing
• /
• v.51 no.3
• /
• pp.334-346
• /
• 2021

Purpose: The purpose of this study was to develop a resilience enhancement program applying mindfulness meditation (REP-MM) and evaluate the effects of the program on post-traumatic stress (PTS), resilience, and health-related quality of life (HRQoL) in patients with ileostomy. Methods: The REP-MM was developed by combining the resilience enhancement program with mindfulness meditation according to four patterns. The program was developed through identifying patients' needs, reviewing relevant literature, developing a preliminary program, and testing content validity and user evaluation. The participants were 55 patients with ileostomy. We conveniently assigned 27 patients to the experimental group and 28 to the control group. The study was conducted in conducted in a hospital from January 22 to May 30, 2019. The REPMM was provided to the experimental group, and conventional ileostomy care was provided to the control group using a nonequivalent control-group pretest-posttest design. Results: ANCOVA revealed that the levels of PTS (F = 321.64, p < .001), resilience (F = 111.86, p < .001), and HRQoL (F = 31.08, p < .001) in the experimental group were higher than those in the control group when comparing pretest to posttest changes. Conclusion: The REP-MM is effective in PTS, resilience, and HRQoL in patients suffering from post-stoma creation crisis. The REP-MM can induce positive self-recognition changes in patients with ileostomy through dispositional, situational, relational, and philosophical interventions. We suggest nurses reduce PTS and improve resilience and HRQoL in patients with ileostomy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.5
• /
• pp.1814-1828
• /
• 2021

Low-light image enhancement is a key technique to overcome the quality degradation of photos taken under scotopic vision illumination conditions. The degradation includes low brightness, low contrast, and outstanding noise, which would seriously affect the vision of the human eye recognition ability and subsequent image processing. In this paper, we propose an approach based on deep learning and Retinex theory to enhance the low-light image, which includes image decomposition, illumination prediction, image reconstruction, and image optimization. The first three parts can reconstruct the enhanced image that suffers from low-resolution. To reduce the noise of the enhanced image and improve the image quality, a super-resolution algorithm based on the Laplacian pyramid network is introduced to optimize the image. The Laplacian pyramid network can improve the resolution of the enhanced image through multiple feature extraction and deconvolution operations. Furthermore, a combination loss function is explored in the network training stage to improve the efficiency of the algorithm. Extensive experiments and comprehensive evaluations demonstrate the strength of the proposed method, the result is closer to the real-world scene in lightness, color, and details. Besides, experiments also demonstrate that the proposed method with the single low-light image can achieve the same effect as multi-exposure image fusion algorithm and no ghost is introduced.

• Clinical Endoscopy
• /
• v.56 no.4
• /
• pp.510-520
• /
• 2023

Background/Aims: We aimed to investigate (1) promising clinical findings for the recognition of focal type autoimmune pancreatitis (FAIP) and (2) the impact of endoscopic ultrasound (EUS)-guided tissue acquisition (EUS-TA) on the diagnosis of FAIP. Methods: Twenty-three patients with FAIP were involved in this study, and 44 patients with resected pancreatic ductal adenocarcinoma (PDAC) were included in the control group. Results: (1) Multivariate analysis revealed that homogeneous delayed enhancement on contrast-enhanced computed tomography was a significant factor indicative of FAIP compared to PDAC (90% vs. 7%, p=0.015). (2) For 13 of 17 FAIP patients (76.5%) who underwent EUS-TA, EUS-TA aided the diagnostic confirmation of AIPs, and only one patient (5.9%) was found to have AIP after surgery. On the other hand, of the six patients who did not undergo EUS-TA, three (50.0%) underwent surgery for pancreatic lesions. Conclusions: Homogeneous delayed enhancement on contrast-enhanced computed tomography was the most useful clinical factor for discriminating FAIPs from PDACs. EUS-TA is mandatory for diagnostic confirmation of FAIP lesions and can contribute to a reduction in the rate of unnecessary surgery for patients with FAIP.

• Journal of the Korea Computer Graphics Society
• /
• v.30 no.2
• /
• pp.11-19
• /
• 2024

Demand for small biomimetic robots that can carry out reconnaissance missions without being exposed to the enemy in underground spaces and narrow passages is increasing in order to increase the fighting power and survivability of soldiers in wartime situations. A small compound eye image sensor for environmental recognition has advantages such as small size, low aberration, wide angle of view, depth estimation, and HDR that can be used in various ways in the field of vision. However, due to the small lens size, the resolution is low, and the problem of resolution in the fused image obtained from the actual compound eye image occurs. This paper proposes a compound eye image quality enhancement algorithm based on Image Enhancement and ESRGAN to overcome the problem of low resolution. If the proposed algorithm is applied to compound eye image fusion images, image resolution and image quality can be improved, so it is expected that performance improvement results can be obtained in various studies using compound eye cameras.

• Tunnel and Underground Space
• /
• v.13 no.5
• /
• pp.373-388
• /
• 2003

The investigation on the rock discontinuity geometry has been usually undergone by direct measurement on the rock exposures. But this sort of field work has disadvantages, which we, for example, restriction of surveying areas and consuming excessive times and labors. To cover these kinds of disadvantages, image processing could be regarded as an altemative way, with additional advantages such as automatic and objective tools when used under adequate computerized algorithm. This study was focused on the recognition of the rock discontinuities captured in the image of rock exposure by digital camera and the production of the discontinuity map automatically. The whole process was written using macro commands builtin image analyzer, ImagePro Plus. ver 4.1(Media Cybernetic). The procedure of image processing developed in this research could be divided with three steps, which are enhancement, recognition and extraction of discontinuity traces from the digital image. Enhancement contains combining and applying several filters to remove and relieve various types of noises from the image of rock surface. For the next step, recognition of discontinuity traces was executed. It used local topographic features characterized by the differences of gray scales between discontinuity and rock. Such segments of discontinuity traces extracted from the image were reformulated using an algorithm of computer decision-making criteria and linked to form complete discontinuity traces. To verify the image processing algorithms and their sequences developed in this research, discontinuity traces digitally photographed on the rock slope were analyzed. The result showed about 75～80% of discontinuities could be detected. It is thought to be necessary that the algorithms and computer codes developed in this research need to be advanced further especially in combining digital filters to produce images to be more acceptable for extraction of discontinuity traces and setting seed pixels automatically when linking trace segments to make a complete discontinuity trace.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.12
• /
• pp.226-235
• /
• 1998

This study proposes the analysis and evaluation of method of time series of ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. The features are extracted from time series data for analysis of weld defects quantitatively. For this purpose, analysis objectives in this study are fractal dimension, Lyapunov exponent, and strange attractor on hyperspace. The Lyapunov exponent is a measure of rate in which phase space diverges nearby trajectories. Chaotic trajectories have at least one positive Lyapunov exponent, and the fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal(correlation) dimensions and Lyapunov exponents show the mean value of 4.663, and 0.093 relatively in case of learning, while the mean value of 4.926, and 0.090 in case of testing in slag inclusion(weld defects) are shown. Therefore, the proposed chaotic feature extraction can be enhancement of precision rate for ultrasonic pattern recognition in defecting signals of weld zone, such as slag inclusion.

• Journal of the Korea Computer Industry Society
• /
• v.3 no.12
• /
• pp.1775-1784
• /
• 2002

Fingerprint recognition technology is used in many biometrics field accordingly essential feature of fingerprint image and the study is progressing. However development is not perfect in performance of the fingerprint recognition and application of the usual life. In the paper, we study various necessity of preprocessing according to algorithm and circumstances of authentication system in automatic information machine. We prove that system circumstance and optation of fingerprints image effectively is the important factor by using optical fingerprint input device and scanning the fingerprint in ID card. And then we present correct and fast computation method for improving image and feature extraction of fingerprint. Also we study effective algorithm implementation of total system.

• Journal of the Korea Computer Industry Society
• /
• v.4 no.4
• /
• pp.647-660
• /
• 2003

The present of state is situation that is realized by necessity of maintenance of public security about great many information is real condition been increasing continually in knowledge info-age been situating in wide field of national defense, public peace, banking, politics, education etc. Also, loss or forgetfulness, and peculation by ID for individual information and number increase of password in Internet called that is sea of information is resulting various social problem. By alternative about these problem, including Biometrics, several authentication systems through sign(Signature), Smart Card, Watermarking technology are developed. Therefore, This paper shows that extract factor that efficiency can get into peculiar feature in physical features for good fingerprint recognition algorithm implementation with old study finding that take advantage of special quality of these fingerprint.