• Title/Summary/Keyword: 영상처리

Search Result 9,266, Processing Time 0.124 seconds

A Study on forest fires Prediction and Detection Algorithm using Intelligent Context-awareness sensor (상황인지 센서를 활용한 지능형 산불 이동 예측 및 탐지 알고리즘에 관한 연구)

  • Kim, Hyeng-jun;Shin, Gyu-young;Woo, Byeong-hun;Koo, Nam-kyoung;Jang, Kyung-sik;Lee, Kang-whan
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.19 no.6
    • /
    • pp.1506-1514
    • /
    • 2015
  • In this paper, we proposed a forest fires prediction and detection system. It could provide a situation of fire prediction and detection methods using context awareness sensor. A fire occurs wide range of sensing a fire in a single camera sensor, it is difficult to detect the occurrence of a fire. In this paper, we propose an algorithm for real-time by using a temperature sensor, humidity, Co2, the flame presence information acquired and comparing the data based on multiple conditions, analyze and determine the weighting according to fire in complex situations. In addition, it is possible to differential management of intensive fire detection and prediction for required dividing the state of fire zone. Therefore we propose an algorithm to determine the prediction and detection from the fire parameters as an temperature, humidity, Co2 and the flame in real-time by using a context awareness sensor and also suggest algorithm that provide the path of fire diffusion and service the secure safety zone prediction.

Development of Landslide Detection Algorithm Using Fully Polarimetric ALOS-2 SAR Data (Fully-Polarimetric ALOS-2 자료를 이용한 산사태 탐지 알고리즘 개발)

  • Kim, Minhwa;Cho, KeunHoo;Park, Sang-Eun;Cho, Jae-Hyoung;Moon, Hyoi;Han, Seung-hoon
    • Economic and Environmental Geology
    • /
    • v.52 no.4
    • /
    • pp.313-322
    • /
    • 2019
  • SAR (Synthetic Aperture Radar) remote sensing data is a very useful tool for near-real-time identification of landslide affected areas that can occur over a large area due to heavy rains or typhoons. This study aims to develop an effective algorithm for automatically delineating landslide areas from the polarimetric SAR data acquired after the landslide event. To detect landslides from SAR observations, reduction of the speckle effects in the estimation of polarimetric SAR parameters and the orthorectification of geometric distortions on sloping terrain are essential processing steps. Based on the experimental analysis, it was found that the IDAN filter can provide a better estimation of the polarimetric parameters. In addition, it was appropriate to apply orthorectification process after estimating polarimetric parameters in the slant range domain. Furthermore, it was found that the polarimetric entropy is the most appropriate parameters among various polarimetric parameters. Based on those analyses, we proposed an automatic landslide detection algorithm using the histogram thresholding of the polarimetric parameters with the aid of terrain slope information. The landslide detection algorithm was applied to the ALOS-2 PALSAR-2 data which observed landslide areas in Japan triggered by Typhoon in September 2011. Experimental results showed that the landslide areas were successfully identified by using the proposed algorithm with a detection rate of about 82% and a false alarm rate of about 3%.

Recognition of dog's front face using deep learning and machine learning (딥러닝 및 기계학습 활용 반려견 얼굴 정면판별 방법)

  • Kim, Jong-Bok;Jang, Dong-Hwa;Yang, Kayoung;Kwon, Kyeong-Seok;Kim, Jung-Kon;Lee, Joon-Whoan
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.21 no.12
    • /
    • pp.1-9
    • /
    • 2020
  • As pet dogs rapidly increase in number, abandoned and lost dogs are also increasing in number. In Korea, animal registration has been in force since 2014, but the registration rate is not high owing to safety and effectiveness issues. Biometrics is attracting attention as an alternative. In order to increase the recognition rate from biometrics, it is necessary to collect biometric images in the same form as much as possible-from the face. This paper proposes a method to determine whether a dog is facing front or not in a real-time video. The proposed method detects the dog's eyes and nose using deep learning, and extracts five types of directional face information through the relative size and position of the detected face. Then, a machine learning classifier determines whether the dog is facing front or not. We used 2,000 dog images for learning, verification, and testing. YOLOv3 and YOLOv4 were used to detect the eyes and nose, and Multi-layer Perceptron (MLP), Random Forest (RF), and the Support Vector Machine (SVM) were used as classifiers. When YOLOv4 and the RF classifier were used with all five types of the proposed face orientation information, the face recognition rate was best, at 95.25%, and we found that real-time processing is possible.

Fair Queuing for Mobile Sink (FQMS) : Scheduling Scheme for Fair Data Collection in Wireless Sensor Networks with Mobile Sink (모바일 싱크를 위한 균등 큐잉(FQMS) : 모바일 싱크 기반 무선 센서 네트워크에서 균등한 데이터 수집을 위한 스케줄링 기법)

  • Jo, Young-Tae;Park, Chong-Myung;Lee, Joa-Hyoung;Seo, Dong-Mahn;Lim, Dong-Sun;Jung, In-Bum
    • Journal of KIISE:Information Networking
    • /
    • v.37 no.3
    • /
    • pp.204-216
    • /
    • 2010
  • Since Sensor nodes around a fixed sink have huge concentrated network traffic, the battery consumption of them is increased extremely. Therefore the lifetime of sensor networks is limited because of huge battery consumption. To address this problem, a mobile sink has been studied for load distribution among sensor nodes. Since a mobile sink changes its location in sensor networks continuously, the mobile sink has time limits to communicate with each sensor node and unstable signal strength from each sensor node. Therefore, a fair and stable data collection method between a mobile sink and sensor nodes is necessary in this environment. When some sensor nodes are not able to send data to the mobile sink, a real-time application in sensor networks cannot be provided. In this paper, the new scheduling method, FQMS (Fair Queuing for Mobile Sink), is proposed for fair and stable data collection for mobile sinks in sensor networks. The FQMS guarantees balanced data collecting between sensor nodes for a mobile sink. In out experiments, the FQMS receives more packets from sensor nodes than legacy scheduling methods and provides fair data collection, because moving speed of a mobile sink, distance between a mobile sink and sensor nodes and the number of sensor nodes are considered.

Image Enhancement of the Weathered Zone and Bedrock Surface with a Radial Transform in Engineering Seismic Data (엔지니어링 탄성파자료에서 방사변환을 통한 풍화대 및 기반암 표면의 영상강화)

  • Kim, Ji-Soo;Jeon, Su-In;Lee, Sun-Joong
    • The Journal of Engineering Geology
    • /
    • v.22 no.4
    • /
    • pp.459-466
    • /
    • 2012
  • A difficulty encountered in engineering seismic mapping is that reflection events from shallow discontinuities are commonly overlapped with coherent noise such as air wave, direct waves, head waves, and high-amplitude surface waves. Here, the radial trace transform, a simple geometric re-mapping of a trace gather (x-t domain) to another trace gather (v-t domain), is applied to investigate the rejection effect of coherent linear noises. Two different types of data sets were selected as a representative database: good-quality data for intermediate sounding (hundreds of meters) in a sedimentary basin and very noisy data for shallow (${\leq}50m$) mapping of the weathered zone and bedrock surface. Results obtained with cascaded application of the radial transform and low-cut filtering proved to be as good as, or better than, those produced using f-k filtering, and were especially effective for air wave and direct wave. This simple transform enables better understanding of the characteristics of various types of noise in the RT domain, and can be generally applied to overcoming diffractions and back-scatterings caused by joints, fractures, and faults commonly that are encountered in geotechnical problems.

Saliency Attention Method for Salient Object Detection Based on Deep Learning (딥러닝 기반의 돌출 객체 검출을 위한 Saliency Attention 방법)

  • Kim, Hoi-Jun;Lee, Sang-Hun;Han, Hyun Ho;Kim, Jin-Soo
    • Journal of the Korea Convergence Society
    • /
    • v.11 no.12
    • /
    • pp.39-47
    • /
    • 2020
  • In this paper, we proposed a deep learning-based detection method using Saliency Attention to detect salient objects in images. The salient object detection separates the object where the human eye is focused from the background, and determines the highly relevant part of the image. It is usefully used in various fields such as object tracking, detection, and recognition. Existing deep learning-based methods are mostly Autoencoder structures, and many feature losses occur in encoders that compress and extract features and decoders that decompress and extend the extracted features. These losses cause the salient object area to be lost or detect the background as an object. In the proposed method, Saliency Attention is proposed to reduce the feature loss and suppress the background region in the Autoencoder structure. The influence of the feature values was determined using the ELU activation function, and Attention was performed on the feature values in the normalized negative and positive regions, respectively. Through this Attention method, the background area was suppressed and the projected object area was emphasized. Experimental results showed improved detection results compared to existing deep learning methods.

Home Network Observation System Using Activate Pattern Analysis of User and Multimedia Streaming (사용자의 행동 패턴 분석과 멀티미디어 스트리밍 기술을 이용한 홈 네트워크 감시 시스템)

  • Oh Dong-Yeol;Oh Hae-Seok;Sung Kyung-Sang
    • Journal of Korea Multimedia Society
    • /
    • v.8 no.9
    • /
    • pp.1258-1268
    • /
    • 2005
  • While the concept of Home Network is laying by and its interests are increasing by means of digitalizing of the information communication infrastructure, many efforts are in progress toward convenient lives. Moreover, as information household appliances which have a junction of connecting to the network are appearing over the past a few years, the demands against intellectual Home Services are increasing. In this paper, by being based upon Multimedia which is an essential factor for developing of various application services on ubiquitous computing environments, we suggest a simplified application model that could apply the information to the automated processing system after studying user's behavior patterns using authentication and access control for identity certification of users. In addition, we compared captured video images in the fixed range by pixel unit through some time and checked disorder of them. And that made safe of user certification as adopting self-developed certification method which was used 'Hash' algorism through salt function of 12 byte. In order to show the usefulness of this proposed model, we did some testing by emulator for control of information after construction for Intellectual Multimedia Server, which ubiquitous network is available on as a scheme so as to check out developed applications. According to experimental results, it is very reasonable to believe that we could extend various multimedia applications in our daily lives.

  • PDF

Effects of Ocean Outfall for Elimination of the Anoxic Layer in Youngsan River Estuary (영산강 하구언에서 저 산소 층의 제거를 위한 해양방류구의 효과)

  • Kwon, Seok-Jae;Cho, Yang-Ki;Seo, Uk-Won
    • Journal of Korean Society of Coastal and Ocean Engineers
    • /
    • v.17 no.4
    • /
    • pp.259-268
    • /
    • 2005
  • There has been a growing interest in the elimination of anoxic layer in the Youngsan River Estuarybecause the anoxic water mass caused mainly by the inflow of fresh water from the sea wall might cause the mass reduction of benthos during summer. An ocean outfall system to discharge treated wastewater into sea water may be used as one of the effective and economical ways to eliminate the anoxic layer. The suitable ocean outfall design is generally proposed for the prediction of the buoyant jet behavior in the near field. The parameters including CTD and current data are taken into account f3r more reliable buoyant jet behavior calculation. One of the numerical models, CORMIX 1, approved by EPA is used herein for the prediction of the trajectorial variation of the cross-sectional salinity and DO concentration distribution on the calculated buoyant jet boundary according to the tidal periods. On the basis of the results, it is suggested that the single port outfall is a useful system to eliminate the anoxic layer. Proper strategies are also proposed for achieving desirable ambient conditions.

A study on the applied Virtual Reality in the On-Line marketing of the shoes (On-Line 신발주문 반품률 제고를 위한 가상현실 적용사례)

  • Choi, Sung-Won
    • Archives of design research
    • /
    • v.17 no.4
    • /
    • pp.191-200
    • /
    • 2004
  • The health of feet is connected with individual's health and affects a man's activity. Shoes need to be designed to protect feet and to absorb the impact of land. Thus, design, comfort and economical efficiency are important factors of shoes. Consumers can choose suitable shoes for their feet in off-line shopping. However, in on-line shopping, because they can not wear shoes, compare to the off-line shopping, there are many problems in internet shopping. First, consumers can get limited information of shoes because they must search information of purchase without other's help. Second, because consumers can not get important information such as design, size and a comfort of wearing, they can not make a careful decision. Above these, the solution of user-oriented internet shopping is development of new type of prototype which is accessible to user and to offer visual information through 3D virtual reality.

  • PDF

An Effective Face Authentication Method for Resource - Constrained Devices (제한된 자원을 갖는 장치에서 효과적인 얼굴 인증 방법)

  • Lee Kyunghee;Byun Hyeran
    • Journal of KIISE:Software and Applications
    • /
    • v.31 no.9
    • /
    • pp.1233-1245
    • /
    • 2004
  • Though biometrics to authenticate a person is a good tool in terms of security and convenience, typical authentication algorithms using biometrics may not be executed on resource-constrained devices such as smart cards. Thus, to execute biometric processing on resource-constrained devices, it is desirable to develop lightweight authentication algorithm that requires only small amount of memory and computation. Also, among biological features, face is one of the most acceptable biometrics, because humans use it in their visual interactions and acquiring face images is non-intrusive. We present a new face authentication algorithm in this paper. Our achievement is two-fold. One is to present a face authentication algorithm with low memory requirement, which uses support vector machines (SVM) with the feature set extracted by genetic algorithms (GA). The other contribution is to suggest a method to reduce further, if needed, the amount of memory required in the authentication at the expense of verification rate by changing a controllable system parameter for a feature set size. Given a pre-defined amount of memory, this capability is quite effective to mount our algorithm on memory-constrained devices. The experimental results on various databases show that our face authentication algorithm with SVM whose input vectors consist of discriminating features extracted by GA has much better performance than the algorithm without feature selection process by GA has, in terms of accuracy and memory requirement. Experiment also shows that the number of the feature ttl be selected is controllable by a system parameter.