• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.83-89
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• 2021

In this paper, we propose an algorithm that provide services to consumers who want to conduct business by scientifically and systematically analyzing the number of pedestrians in a specific area over a specific period of time. In this paper, we proposed the algorithm to analyze the commercial area using the pedestrian-detect algorithm in the particular region using YOLO, one of the deep learning techniques. And with one image per minute in the images, the number of pedestrians is identified and this information is used for the analysis of business district on interesting area and time, systematically and objectively.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.596-600
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• 2010

This paper proposes hough transform-based semi-automatic vertex detection algorithm for object modeling on a mobile phone supporting touch-screens. The proposed algorithm shows fast processing time by searching the limited range of parameters for computing hough transform with a small range of ROI image. Moreover, the proposed algorithm removes bad candidates among the detected lines by selecting the two closest candidate lines from the position of user's input. After that, it accurately detects an interesting vertex without additionally required interactions by detecting an intersection point of the two lines. As a result, we believe that the proposed algorithm shows a 1.4 pixel distance error on average as a vertex detection accuracy under such conditions as a 5.7 pixel distance error on average as an inaccurate input.

• Journal of Korea Water Resources Association
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• v.47 no.12
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• pp.1107-1119
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• 2014

Interesting in abnormal climate is currently growing because of climate change. With this, an increasing number of people continue to show concern over the negative effects of such changes. In Korea, the annual average rainfall amount increased to about 19% from 1,155 mm in the 1910s to 1,375 mm in the 2000s. By the end of the 21st century, it has been projected that rainfall will further increase to about 17%. In particular, the 10-year frequency of localized heavy rain of more than 100-mm rainfall per day reached 385 days in the last 10 years. As such, it increased 1.7 times from 222 in the 1970s-80s. The extreme events caused by climate change is thus reported as having exacerbated over the years. Gangwon-province will suffer more from climate change than any other region in Korea because of its mostly mountainous terrain. It is a special region with both mountainous and oceanic climates divided alongside the eastern and western regions of the Taebaek Mountain Range. As such, this paper try to quantify using ETCCDI (Expert Team on Climate Change Detection and Indices) the recent climate changes in this region.

• The Korean Journal of Ceramics
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• v.2 no.3
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• pp.137-141
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• 1996

Ambient air aged anodically etched porous silicon (PS) and spark-processed silicon (sp-Si) show interesting similarities and dissimilarities in some of their luminescence-related properties. Among these similarties are: (1) the photoluminescence (PL) peak maximum in the blue/violet (410 nm);(2) the blue/violet PL peak positions are essentially unchanged with temperature ; (3) PL decay times in the nanosecond region which are independent of the detection wavelength, which is much faster in decay times compared to that of observed decay time in $SiO_2$.Among the dissimilarities are: (1) the PL intensity of blue/violet luminescence, namely, the PL intensity of sp-Si is at least 2 orders of magnitude larger than that of an ambient air aged PS; (2) the blue/violet PL intensity of sp-Si is more stable than that of ambient air aged PS under UV illuminations; (3) FTIR spectra of sp-Si favor those modes, which involve silicon -oxygen bonds in $SiO_2$ stoichiometry, whereas ambient air aged PS can be considered as a nonstoichiometric oxide judging from the observed vibrational spectra.

• Journal of Veterinary Clinics
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• v.25 no.3
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• pp.176-181
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• 2008

Fluid accumulation within the tympanic bulla is an important diagnostic indicator of canine otitis media although its identification can be a challenge using currently available imaging techniques. The purpose of this study was to compare radiography, computed tomography (CT) and magnetic resonance imaging (MRI) in the identification of fluid accumulation within canine tympanic bulla. Unilateral tympanic bulla in 10 beagles were experimentally filled with blood or saline. Quantitative analysis of CT images were obtained by using Hounsfield unit (HU). MR signal intensity was obtained by using region of interesting (ROI) and compared with those of gray matter. On the CT image, the presence of blood or saline produced a fluid opacity occupying the tympanic bulla. On the MR image, the appearance of blood in the tympanic bulla was isointense in T1-weighted images and hyperintense in T2-weighted images. However, the appearance of saline in the tympanic bulla was hypointense in T1-weighted images and hyperintense in T2-weighted images. This study suggest that CT and MR imaging are useful methods for detection and differentiation of fluid in canine tympanic bulla.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.322-325
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• 2018

영상의 관심 영역 검출은 영상처리 및 컴퓨터 비전 응용 분야에서 꾸준하게 사용되고 있는 기법이다. 특히, 근래 심층신경망 연구의 급격한 발전에 힘입어 심층신경망을 이용한 관심 영역 검출 기법에 대한 연구가 활발하게 진행되고 있다. 한편 Fully Convolutional Network(이하 FCN)은 본래 심층 예측(Dense Prediction)을 통한 의미론적 영상 분할(Semantic Segmentation)을 수행하기 위해 제안된 심층신경망 구조이다. FCN을 영상의 관심 영역 검출에 활용하여도 기존 관심 영역 검출 기법과 비교하여 충분히 좋은 성능을 발휘할 수 있다. 그러나 FCN에 사용되는 convolution 층의 수가 많고, 이에 따른 가중치(weight)의 개수도 기하급수적으로 늘어나 검출에 필요한 시간 복잡도가 매우 크다는 문제점이 있다. 따라서 본 논문에서는 기존 FCN이 가진 검출 시간 복잡도의 문제점을 convolution 층의 가중치 관점에서 해결하고자 이를 조절하여 FCN의 관심 영역 검출 속도를 향상시키는 방법을 제안한다. 적절한 convolution 층의 가중치를 조절함으로써, MSRA10K 데이터셋 환경에서 검출 정확도를 크게 저하시키지 않고도 최대 약 20.5%만큼 검출 속도를 향상시킬 수 있었다.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.163-170
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• 2017

Internet of things (IoT) is a new paradigm for collecting, processing and analyzing various contents in order to detect anomalies and to monitor particular patterns in a specific environment. The collected data can be used to discover new patterns and to offer new insights. IoT-enabled data mashup is a new technology to combine various types of information from multiple sources into a single web service. Mashup services create a new horizon for different applications. Environmental monitoring is a serious tool for the state and private organizations, which are located in regions with environmental hazards and seek to gain insights to detect hazards and locate them clearly. These organizations may utilize IoT - enabled data mashup service to merge different types of datasets from different IoT sensor networks in order to leverage their data analytics performance and the accuracy of the predictions. This paper presents an IoT - enabled data mashup service, where the multimedia data is collected from the various IoT platforms, then fed into an environmental cognition service which executes different image processing techniques such as noise removal, segmentation, and feature extraction, in order to detect interesting patterns in hazardous areas. The noise present in the captured images is eliminated with the help of a noise removal and background subtraction processes. Markov based approach was utilized to segment the possible regions of interest. The viable features within each region were extracted using a multiresolution wavelet transform, then fed into a discriminative classifier to extract various patterns. Experimental results have shown an accurate detection performance and adequate processing time for the proposed approach. We also provide a data mashup scenario for an IoT-enabled environmental hazard detection service and experimentation results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.61-69
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• 2010

This paper presents an efficient object selection algorithm by analyzing and detecting of human activity. Generally, when people point any something, they will put a face on the target direction. Therefore, the direction of the face and fingers and was ordered to be connected to a straight line. At first, in order to detect the moving objects from the input frames, we extract the interesting objects in real time using background subtraction. And the judgment of movement is determined by Principal Component Analysis and a designated time period. When user is motionless, we estimate the user's indication by estimation in relation to vector from the head to the hand. Through experiments using the multiple views, we confirm that the proposed algorithm can estimate the movement and indication of user more efficiently.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.293-300
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• 2013

Road signs are important infrastructures for safe and smooth traffic by providing useful information to drivers. It is necessary to establish road sign DB for managing road signs systematically. To provide such DB, manually detection and recognition from imagery can be done. However, it is time and cost consuming. In this study, we proposed algorithms for automatic recognition of direction information in road sign image. Also we developed algorithm code using OpenCV library, and applied it to road sign image. To automatically detect and recognize direction information, we developed program which is composed of various modules such as image enhancement, image binarization, arrow region extraction, interesting point extraction, and template image matching. As a result, we can confirm the possibility of automatic recognition of direction information in road sign image.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.63.2-63.2
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• 2014

As a part of the "Dust, Ice, and Gas In Time" (DIGIT) key program on Herschel, we observed GSS30-IRS1, a Class I protostar located in Ophiuchus (d =125 pc), with Herschel/Photodetector Array Camera and Spectrometer (PACS). More than 70 lines were detected within a wavelength range from 50 ${\mu}m$ to 200 ${\mu}m$: CO lines from J = 14-13 to 41-40, several $H_2O$ lines of Eup = 100 K to 1500 K, 16 transitions of OH rotational lines, and two atomic [O I] lines at 63 and 145 ${\mu}m$. The [C II] line, known as a tracer of externally heated gas by the interstellar radiation field, is also detected at 158 ${\mu}m$. All lines, except [O I] and [C II], are detected only at the central spaxel of $9^{\prime\prime}.4{\times}9^{\prime\prime}.4$. The [O I] emission is extended along a NE-SW orientation, which is consistent with the known outflow direction, while the [C II] line is detected over all spaxels. One possible explanation of the detection of the [C II] line and no correlation of its spatial distribution with any other molecular emission is the existence of the enhanced ISRF nearby GSS30-IRS1. One interesting feature of GSS30-IRS1 is that the continuum emission is extended beyond the point-spread function (PSF), unlike the molecular line emission, indicative of significant external heating. The best-fit continuum model of GSS30-IRS1 with the physical structure including flared disk, envelope, and outflow shows that the internal luminosity is 11 $L_{\odot}$, and the region is also externally heated by a radiation field enhanced by a factor of 25 compared to the local standard interstellar field.