• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.8
• /
• pp.1655-1666
• /
• 2015

In this paper, user-position estimation method is proposed by using a single camera for both indoor and outdoor environments. Conventionally, the GPS of RF-based estimation methods have been widely studied in the literature for outdoor and indoor environments, respectively. Each method is useful only for indoor or outdoor environment. In this context, this study adopts a vision-based approach which can be commonly applicable to both environments. Since the distance or position cannot be extracted from a single still image, the reference images pro-stored in image database are used to identify the current position from the single still image captured by a single camera. The reference image is tagged with its captured position. To find the reference image which is the most similar to the current image, the SURF algorithm is used for feature extraction. The outliers in extracted features are discarded by using RANSAC algorithm. The performance of the proposed method is evaluated for two buildings and their outsides for both indoor and outdoor environments, respectively.

• Journal of radiological science and technology
• /
• v.32 no.1
• /
• pp.17-24
• /
• 2009

Noise evaluation for an image has been performed by root mean square (RMS) granularity, autocorrelation function (ACF), and Wiener spectrum. RMS granularity stands for standard deviation of photon data and ACF is acquired by integration of 1 D function of distance variation. Fourier transform of ACF results in noise power spectrum which is called Wiener spectrum in image quality evaluation. Wiener spectrum represents noise itself. In addition, along with MTF, it is an important factor to produce detective quantum efficiency (DQE). The proposed evaluation method using Wiener spectrum is expected to contribute to educate the concept of Wiener spectrum in educational organizations, choose the appropriate imaging detectors for clinical applications, and maintain image quality in digital imaging systems.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2011.07a
• /
• pp.454-455
• /
• 2011

미토콘드리아의 수송은 치매, 다형성 경화증, 알츠하이머병 등의 신경성 질환과 관련하여 활발하게 연구되고 있다. 하지만 미토콘드리아 영상의 경우 일반 영상에 비해 노이즈(noise)가 많고 초당 프레임 수(frame-persecond)가 낮기 때문에 분석이 쉽지 않다. 이에 따라 미토콘드리아의 수송 통로인 축색돌기(axon)를 사전에 검출하고자 하는 연구들이 진행되고 있다. 본 논문에서는 이러한 배경을 바탕으로 미토콘드리아 영상에서 축색돌기를 자동으로 분리, 검출해내는 알고리즘을 제안한다. 배경이 비해 밝게 착색되어 있다는 미토콘드리아의 특성을 이용하여 축색돌기를 구분하는 데에 최대 화소값 기법(maximum intensity)과 혈관 증폭 필터(vessel enhancement filter)를 이용한다. 두 기법을 통해 얻은 축색돌기의 파편들은 로젠펠드 세선화(rosenfeld thinning)와 선형 보간법(linear interpolation)을 이용하여 연결되고 최종적인 검출 결과를 얻어낸다. 제시된 실험결과는 영상에서 전체적인 축색돌기가 성공적으로 검출되고 있음을 보여준다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.04a
• /
• pp.576-579
• /
• 2004

Eventhough the productivity has been improved remarkably by introducing automatic facilities, the 100％ inspection is necessary because the possibility to produce large amount of defective goods is also increased. Since it is extremely unreasonable that workers inspect very large amount of products as 100％ inspection, there has been many researches for the automatic inspection system. In this thesis, we develop an automatic detection system of suspension insulator's minutes cracks System The automatic detection system of suspension insulator's minute cracks： To detect the minute cracks of suspension insulators, images of the insulator are acquired with a progressive scan camera, rotating a suspension insulator on a turning table. And after the shadow and noises are eliminated by preprocessing techniques, we detect minute cracks using the features of them.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.594-597
• /
• 2010

This paper proposes a fire detection algorithm using low-cost camera to detect visual features of fire. In the previous work sensor cameras were used, but here we use very simple cameras. This method uses YCbCr and YIQ color model to detect candidate regions of fire. The candidate areas are extracted from the boundaries of the fire. noise removal elimination is performed. Regardless of environmental changes around the fire area, the results of the proposed algorithm are very satisfactory.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.5
• /
• pp.615-621
• /
• 2009

TFT-LCD image consists of ununiform background, random noises and target defect signal components. Defects in TFT-LCD have some intensity variations compared to background region. It is sometimes difficult for human inspectors to figure out. In this paper, we propose multi-level threshold scheme for detection of the real defect using probability density function with Parzen Window. The experimental results show that the proposed algorithms produce promising results and can be applied to automated inspection systems for finding defects in the TFT-LCD image.

• Journal of the Institute of Convergence Signal Processing
• /
• v.14 no.1
• /
• pp.27-32
• /
• 2013

It plays an important role to detect the shape of an ellipse in many application areas of image processing. But it is very difficult to detect the ellipse in the real image because the noise was involved in the image, other objects obscured the ellipse or the ellipses were overlap with each other. In this paper, we extract the boundary (edge) to detect ellipse in the image and perform the grouping process in order to reduce amount of information. As a result, the speed of the ellipse detection was improved. Also in order to the ellipse detection, we selected the five ellipse parameters at random And then to select the optimal parameters of the ellipse, the linear least-squares approximation is applied. To verify the ellipse detection, RANSAC algorithm is applied. After the algorithm proposed in this study was implemented, the results applied to the real images showed an aocuracy of 75% and speed was very fast to compared with other researches. It mean that the proposed algorithm was valuable to detect the ellipses in the image.

• Journal of Digital Contents Society
• /
• v.18 no.5
• /
• pp.989-994
• /
• 2017

In this paper, we propose a pothole detection system using 2D LiDAR and a pothole detection algorithm. Conventional pothole detection methods can be divided into vibration-based method, 3D reconstruction method, and vision-based method. Proposed pothole detection system uses two inexpensive 2D LiDARs and improves pothole detection performance. Pothole detection algorithm is divided into preprocessing for noise reduction, clustering and line extraction for visualization, and gradient function for pothole decision. By using gradient of distance data function, we check the existence of a pothole and measure the depth and width of the pothole. The pothole detection system is developed using two LiDARs, and the 3D pothole detection performance is shown by detecting a pothole with moving LiDAR system.

• Smart Media Journal
• /
• v.9 no.4
• /
• pp.134-143
• /
• 2020

Vehicle License Plate Recognition is one of the approaches for transportation and traffic safety networks, such as traffic control, speed limit enforcement and runaway vehicle tracking. Although it has been studied for decades, it is attracting more and more attention due to the recent development of deep learning and improved performance. Also, it is largely divided into license plate detection and recognition. In this study, experiments were conducted to improve license plate detection performance by utilizing various object detection methods and WPOD-Net(Warped Planar Object Detection Network) model. The accuracy was improved by selecting the method of detecting the vehicle(s) and then detecting the license plate(s) instead of the conventional method of detecting the license plate using the object detection model. In particular, the final performance was improved through the process of removing noise existing in the image by using the Fast-SRGAN model, one of the Super-Resolution methods. As a result, this experiment showed the performance has improved an average of 4.34% from 92.38% to 96.72% compared to previous studies.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1556-1557
• /
• 2011

변압기의 고체 절연이 열화 되거나 불순물 및 수분이 혼입되어 임계치 이상의 고전계가 인가되면 결합부분에서 부분방전이 발생한다. 현재 변압기에서 부분방전을 검출하기 위해서는 부싱탭을 이용하거나 전류센서, 초음파센서 등을 이용하여 부분방전을 검출하고 있지만 전기적인 부싱탭이나 전류센서를 이용한 검출 방법은 주변 잡음의 영향을 많이 받고 초음파법은 감도가 낮다는 단점을 가지고 있다. 이에, UHF 방식을 이용한 부분방전 검출 기술이 전력기기의 초기 고장진단을 발견하는 효과적인 방법으로 인식되고 있다. 최근에는 이러한 UHF 진단방식의 높은 감도, 외부노이즈에 대한 적은 영향, 온라인 측정의 가능성의 장점으로 전력용 변압기에도 적용되고 있다. 본 논문에서는 전력 변압기에서 PD 진단에 적합한 UHF 센서의 개발에 대해서 소개한다. 제안된 UHF 센서는 광대역(500 ~ 1,500MHz)에서 측정이 가능하며 감도가 우수하며 특정 대역에서 공진점을 가지는 다중 공진 모노폴 안테나 타입이다. 안테나 시뮬레이션 및 해석을 통해 유중 부분방전을 모의하여 감도 측정을 실시한 결과 제안된 UHF 센서가 전력용 변압기의 부분방전 측정에서 높은 감도를 나타냈으며, 기존 측정 방식의 단점을 보완할 수 있는 방안으로서 전자파를 이용한 부분방전 측정에 대한 기초연구를 실시하여 변압기 운전중에 전자파 측정에 의한 부분방전 감시가 가능한 것으로 나타났다.