• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.5
• /
• pp.859-866
• /
• 2023

This paper focuses on configuring a user-friendly system of LED systems by applying improvement measures such as gamma correction, non-flicker, and driving noise removal using MCUs and LED drivers. As a result of the experiment, the 22kHz PWM mode of the LED driver generated noise outside the audible frequency range, making it practically imperceptible to users. The appropriate pull-up resistor values within the normal operating delay ratio of 5% were found to be 1kΩ to 10kΩ for the 3kHz PWM mode and 1kΩ to 2kΩ for the 22kHz PWM mode. In addition, gamma correction can be optimized for nonlinear human visual systems to express accurate contrast and as a result, it is expected to develop an LED system that can be expressed more naturally and accurately than conventional LED systems and improve users' visual experience.

• Journal of the Korea Institute of Building Construction
• /
• v.24 no.2
• /
• pp.261-271
• /
• 2024

The widespread adoption of aluminum slab formwork in modern construction, evident in both domestic and international projects, offers numerous advantages. However, a critical challenge persists regarding the dismantling process for these slabs. The current industry standard involves dropping the slabs to the ground floor upon removal. This practice raises several concerns, notably the generation of significant noise pollution that disrupts nearby communities. More importantly, the risk of worker injuries due to falls from height during the dismantling process is a serious safety hazard. Additionally, the impact from dropping the slabs can damage the aluminum itself, leading to increased replacement costs. These drawbacks necessitate the exploration of alternative dismantling techniques that prioritize worker safety, material sustainability, and overall process efficiency. Accordingly, in this study, when the entire first-generation slab formwork of an apartment house is simultaneously lowered to a reachable position for workers, it is then disassembled and lifted for transport to the next floor. This approach has the potential to demonstrate improvements in safety, quality, economy, and process efficiency.

• International Journal of Computer Science & Network Security
• /
• v.24 no.2
• /
• pp.158-168
• /
• 2024

There is hardly any person in modern times who has not taken soft drinks instead of drinking water. The rate of people taking soft drinks being surprisingly high, researchers around the world have cautioned from time to time that these drinks lead to weight gain, raise the risk of non-communicable diseases and so on. Therefore, in this work an image-based tool is developed to monitor the nutritional information of soft drinks by using deep convolutional neural network with transfer learning. At first, visual saliency, mean shift segmentation, thresholding and noise reduction technique, collectively known as 'pre-processing' are adopted to extract the location of drinks region. After removing backgrounds and segment out only the desired area from image, we impose Discrete Wavelength Transform (DWT) based resolution enhancement technique is applied to improve the quality of image. After that, transfer learning model is employed for the classification of drinks. Finally, nutrition value of each drink is estimated using Bag-of-Feature (BoF) based classification and Euclidean distance-based ratio calculation technique. To achieve this, a dataset is built with ten most consumed soft drinks in Bangladesh. These images were collected from imageNet dataset as well as internet and proposed method confirms that it has the ability to detect and recognize different types of drinks with an accuracy of 98.51%.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.1
• /
• pp.15-26
• /
• 2013

This paper proposes a classification method of parallel, vertical parking states and pillars for parking assist system using ultrasonic sensors. Since, in general parking space detection module, the compressed amplitude of ultrasonic data are received, the analysis of them is difficult. To solve these problems, in preprocessing state, symmetric transform and noise removal are performed. In feature extraction process, four features, standard deviation of distance, reconstructed peak, standard deviation of reconstructed signal and sum of width, are proposed. Gaussian fitting model is used to reconstruct saturated peak signal and discriminability of each feature is measured. To find the best combination among these features, multi-class SVM and subset generator are used for more accurate and robust classification. The proposed method shows 92 % classification rate and proves the applicability to parking space detection modules.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.321-325
• /
• 2004

Retinopathy of Prematurity (ROP) is a common retinal neovascular disorder of premature infants. It can be characterized by inappropriate and disorganized vessel. This paper present a method for blood vessel detection on infant retinal images. The algorithm is designed to detect the retinal vessels. The proposed method applies a Lapalacian of Gaussian as a step-edge detector based on the second-order directional derivative to identify locations of the edge of vessels with zero crossings. The procedure allows parameters computation in a fixed number of operations independent of kernel size. This method is composed of four steps : grayscale conversion, edge detection based on LOG, noise removal by adaptive Wiener filter & median filter, and Otsu's global thresholding. The algorithm has been tested on twenty infant retinal images. In cooperation with the Digital Imaging Research Centre, Kingston University, London and Department of Opthalmology, Imperial College London who supplied all the images used in this project. The algorithm has done well to detect small thin vessels, which are of interest in clinical practice.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.154-154
• /
• 2017

Root is an important organ of plant that typically lies below the surface of the soil. Root surface determines the ability of plants to absorb nutrient and water from the surrounding soil. This study describes an application of image processing and computer vision which was implemented for rapid measurement of seed germination such as root length, surface area, average diameter, branching points of roots. A CCD camera was used to obtain RGB image of seed germination which have been planted by wet paper in a humidity chamber. Temperature was controlled at approximately 250C and 90% relative humidity. Pre-processing techniques such as color space, binarized image by customized threshold, removal noise, dilation, skeleton method were applied to the obtained images for root segmentation. The various morphological parameters of roots were estimated from a root skeleton image with the accuracy of 95% and the speed of within 10 seconds. These results demonstrated the high potential of computer vision technique for the measurement of seed germination.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2008.11a
• /
• pp.109-112
• /
• 2008

최근 MPEG(moving picture experts group)에서 표준화를 진행하고 있는 3차원 비디오 시스템은 다시점 영상과 깊이영상을 동시에 이용하여 사용자가 임의의 시점을 선택하거나 스테레오스코픽 장치와 같은 3차원 영상 재생장 치를 동해 3차원 영상을 제공하는 차세대 방송 시스템이다 제한된 시점수를 이용하여 보다 많은 시점의 영상을 제공하려면 중간시점의 영상을 보간하는 장치가 필수적이다. 이 시스템의 입력정보인 깊이값을 이용하면 시점이동을 쉽게 할 수 있는데, 보간한 영상의 화질은 이 깊이값의 정확도에 따라 결정된다. 깊이맵은 대개 컴퓨터 비전을 기반으로 한 스테레오 정합기술을 이용 획득하는데, 객체의 경계와 같은 깊이값 불연속 영역에서 주로 깊이값 오류가 발생하게 된다. 이런 오류는 생성한 중간영상의 배경에 원치 않는 잡음을 발생시킨다. 기존의 방법에서는 측정한 깊이법의 객체 경계와 영상의 객체 경계가 일치한다는 가정으로 중간영상을 합성했다. 그러나 실제로는 깊이값 측정 과정에서 두 가지 경계가 일치하지 않아 전경의 일부분이 배경으로 합성되어 잡음을 발생하는 것이다. 본 논문에서는 깊이맵을 기반으로 중간시점의 영상을 보간할 때 발생하는 경계 잡음을 처리하는 방법을 제안한다. 중간영상을 합성할 때 비폐색 영역을 합성한 후 경계 잡음이 발생할 수 있는 영역을 비폐색 영역을 따라 구별한 다음, 잡음이 없는 참조 영상을 이용함으로써 경계 잡음을 처리할 수 있다. 실험 결과를 통해 배경 잡음이 사라진 자연스러운 합성영상을 생성했다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.13 no.1
• /
• pp.67-72
• /
• 2013

Cloud detection and analysis from satellite images has been a topic of research in many atmospheric and environmental studies; however, it still is a challenging task for many reasons. In this paper, we propose a new method for cloud-type classification using fuzzy logic. Knowing that visible-light images of clouds contain thickness related information, while infrared images haves height-related information, we propose a two-layered fuzzy logic based on the input source to provide us with a relatively clear-cut threshold in classification. Traditional noise-removal methods that use reflection/release characteristics of infrared images often produce false positive cloud areas, such as fog thereby it negatively affecting the classification accuracy. In this study, we used the color information from source images to extract the region of interest while avoiding false positives. The structure of fuzzy inference was also changed, because we utilized three types of source images: visible-light, infrared, and near-infrared images. When a cloud appears in both the visible-light image and the infrared image, the fuzzy membership function has a different form. Therefore we designed two sets of fuzzy inference rules and related classification rules. In our experiment, the proposed method was verified to be efficient and more accurate than the previous fuzzy logic attempt that used infrared image features.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.9
• /
• pp.3578-3582
• /
• 2010

The nitrogen oxidized substance(NOx) from cars in city is one of serious air-polution problems. In advanced country, the powder or the liquid photocatalystic for asphalt pavement and noise barrier have been used to reduce the air-polution. In this paper, the effect of photocatalystic on asphalt pavement has been evaluated, especially for UV optical science reactions analyzed NOx purification efficiencies of the automobile waste gas. Judging from the limited lab-scale test, the use of the powder or the liquid photocatalystic is one of alternatives to reduce the NOx from automobile.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.66 no.4
• /
• pp.200-205
• /
• 2017

In this paper, we propose a technique to determine the normal and arc of an alternating current using a mixed filter composed of an average filter and a band-pass filter and a frequency analysis. The proposed method uses the moving average filter of the FIR filter structure for noise removal and the band-pass filter of the IIR filter structure for detecting only specific frequency components after normalizing the measured current signal based on the maximum value. After performing Fast Fourier Transform (FFT) using the band-pass filtered signal, the total energy is calculated using the magnitude component of the frequency, and the arc is detected using the magnitude of the calculated energy. In order to show the validity of the proposed method, we experimented with various data and found that arc and steady state can be easily discriminated by calculating spectral energy. Therefore, it is considered that the proposed method can be applied to arc diagnosis of low voltage electric wire.