• Title/Summary/Keyword: automatic detection

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AUTOMATIC MOTION DETECTION USING FALSE BACKGROUND ELIMINATION

  • Seo, Jin Keun;Lee, Sukho
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.17 no.1
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    • pp.47-54
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    • 2013
  • This work deals with automatic motion detection for with surveillance tracking that aims to provide high-lighting movable objects which is discriminated from moving backgrounds such as moving trees, etc. For this aim, we perform a false background region detection together with an initial foreground detection. The false background detection detects the moving backgrounds, which become eliminated from the initial foreground detection. This false background detection is done by performing the bimodal segmentation on a deformed image, which is constructed using the information of the dominant colors in the background.

Design and Implementation of the Smart Fire Detection System and Automatic Extinguish Device Interface Platform based on Thermal Imaging Camera (적외선 열 영상 카메라 기반의 스마트 화재감지 시스템 및 자동소화 장치 인터페이스 플랫폼의 설계 및 구현)

  • Chang, Rak-Ju;Lee, Soon-Yi;Kang, Suk-Won;Lee, Dong Myung
    • Proceedings of the Korea Contents Association Conference
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    • 2014.11a
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    • pp.7-8
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    • 2014
  • The smart fire detection and automatic extinguish device interface platform based on thermal imaging camera that early monitors fire is designed and implemented in this paper. If a fire occurs in some area, the developed system can detect and automatically extinguish the fire. The major functions for developing the system are: Image system and Viewer for fire detection based on Thermal imaging camera and Megapixel camera; Automatic extinuish device for early fir detection; Interface platform between monitoring systems and automatic extinguish device.

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Automatic Speechreading Feature Detection Using Color Information (색상 정보를 이용한 자동 독화 특징 추출)

  • Lee, Kyong-Ho;Yang, Ryong;Rhee, Sang-Burm
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.6
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    • pp.107-115
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    • 2008
  • Face feature detection plays an important role in application such as automatic speechreading, human computer interface, face recognition, and face image database management. We proposed a automatic speechreading feature detection algorithm for color image using color information. Face feature pixels is represented for various value because of the luminance and chrominance in various color space. Face features are detected by amplifying, reducing the value and make a comparison between the represented image. The eye and nose position, inner boundary of lips and the outer line of the tooth is detected and show very encouraging result.

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Class Knowledge-oriented Automatic Land Use and Land Cover Change Detection

  • Jixian, Zhang;Yu, Zeng;Guijun, Yang
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.47-49
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    • 2003
  • Automatic land use and land cover change (LUCC) detection via remotely sensed imagery has a wide application in the area of LUCC research, nature resource and environment monitoring and protection. Under the condition that one time (T1) data is existed land use and land cover maps, and another time (T2) data is remotely sensed imagery, how to detect change automatically is still an unresolved issue. This paper developed a land use and land cover class knowledge guided method for automatic change detection under this situation. Firstly, the land use and land cover map in T1 and remote sensing images in T2 were registered and superimposed precisely. Secondly, the remotely sensed knowledge database of all land use and land cover classes was constructed based on the unchanged parcels in T1 map. Thirdly, guided by T1 land use and land cover map, feature statistics for each parcel or pixel in RS images were extracted. Finally, land use and land cover changes were found and the change class was recognized through the automatic matching between the knowledge database of remote sensing information of land use & land cover classes and the extracted statistics in that parcel or pixel. Experimental results and some actual applications show the efficiency of this method.

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Remote Distance Measurement from a Single Image by Automatic Detection and Perspective Correction

  • Layek, Md Abu;Chung, TaeChoong;Huh, Eui-Nam
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.8
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    • pp.3981-4004
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    • 2019
  • This paper proposes a novel method for locating objects in real space from a single remote image and measuring actual distances between them by automatic detection and perspective transformation. The dimensions of the real space are known in advance. First, the corner points of the interested region are detected from an image using deep learning. Then, based on the corner points, the region of interest (ROI) is extracted and made proportional to real space by applying warp-perspective transformation. Finally, the objects are detected and mapped to the real-world location. Removing distortion from the image using camera calibration improves the accuracy in most of the cases. The deep learning framework Darknet is used for detection, and necessary modifications are made to integrate perspective transformation, camera calibration, un-distortion, etc. Experiments are performed with two types of cameras, one with barrel and the other with pincushion distortions. The results show that the difference between calculated distances and measured on real space with measurement tapes are very small; approximately 1 cm on an average. Furthermore, automatic corner detection allows the system to be used with any type of camera that has a fixed pose or in motion; using more points significantly enhances the accuracy of real-world mapping even without camera calibration. Perspective transformation also increases the object detection efficiency by making unified sizes of all objects.

Automatic Visual Inspection System -Detection of Insulator′s Minute Crack- (자동 시각 검사 시스템 -현수애자의 미세균열 검출-)

  • 이상용;김용철
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.04a
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    • pp.576-579
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    • 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.

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Hybrid Fuzzy Adaptive Wiener Filtering with Optimization for Intrusion Detection

  • Sujendran, Revathi;Arunachalam, Malathi
    • ETRI Journal
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    • v.37 no.3
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    • pp.502-511
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    • 2015
  • Intrusion detection plays a key role in detecting attacks over networks, and due to the increasing usage of Internet services, several security threats arise. Though an intrusion detection system (IDS) detects attacks efficiently, it also generates a large number of false alerts, which makes it difficult for a system administrator to identify attacks. This paper proposes automatic fuzzy rule generation combined with a Wiener filter to identify attacks. Further, to optimize the results, simplified swarm optimization is used. After training a large dataset, various fuzzy rules are generated automatically for testing, and a Wiener filter is used to filter out attacks that act as noisy data, which improves the accuracy of the detection. By combining automatic fuzzy rule generation with a Wiener filter, an IDS can handle intrusion detection more efficiently. Experimental results, which are based on collected live network data, are discussed and show that the proposed method provides a competitively high detection rate and a reduced false alarm rate in comparison with other existing machine learning techniques.

Implementation of Effective Automatic Foreground Motion Detection Using Color Information

  • Kim, Hyung-Hoon;Cho, Jeong-Ran
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.6
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    • pp.131-140
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    • 2017
  • As video equipments such as CCTV are used for various purposes in fields of society, digital video data processing technology such as automatic motion detection is essential. In this paper, we proposed and implemented a more stable and accurate motion detection system based on background subtraction technique. We could improve the accuracy and stability of motion detection over existing methods by efficiently processing color information of digital image data. We divided the procedure of color information processing into each components of color information : brightness component, color component of color information and merge them. We can process each component's characteristics with maximum consideration. Our color information processing provides more efficient color information in motion detection than the existing methods. We improved the success rate of motion detection by our background update process that analyzed the characteristics of the moving background in the natural environment and reflected it to the background image.