Enhancement of vision systems based on runway detection by image processing techniques

被引:0
|
作者
Gulec, N. [1 ]
Sen Koktas, N. [1 ]
机构
[1] METU Technopolis, SDT Space & Def Technol Inc, TR-06531 Ankara, Turkey
来源
AIRBORNE INTELLIGENCE, SURVEILLANCE, RECONNAISSANCE (ISR) SYSTEMS AND APPLICATIONS IX | 2012年 / 8360卷
关键词
Combined vision systems; degraded visual environments; approach and landing; runway detection; image processing;
D O I
10.1117/12.923697
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
An explicit way of facilitating approach and landing operations of fixed-wing aircraft in degraded visual environments is presenting a coherent image of the designated runway via vision systems and hence increasing the situational awareness of the flight crew. Combined vision systems, in general, aim to provide a clear view of the aircraft exterior to the pilots using information from databases and imaging sensors. This study presents a novel method that consists of image-processing and tracking algorithms, which utilize information from navigation systems and databases along with the images from daylight and infrared cameras, for the recognition and tracking of the designated runway through the approach and landing operation. Video data simulating the straight-in approach of an aircraft from an altitude of 5000 ft down to 100 ft is synthetically generated by a COTS tool. A diverse set of atmospheric conditions such as fog and low light levels are simulated in these videos. Detection and false alarm rates are used as the primary performance metrics. The results are presented in a format where the performance metrics are compared against the altitude of the aircraft. Depending on the visual environment and the source of the video, the performance metrics reach up to 98% for DR and down to 5% for FAR.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Runway Obstacle Detection for Flight Vision Systems
    Andreev, Denis S.
    PROCEEDINGS OF THE 2021 IEEE CONFERENCE OF RUSSIAN YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING (ELCONRUS), 2021, : 1596 - 1598
  • [2] Image Processing Techniques for UAV Vision-Based River Floating Contaminant Detection
    Lin, Youxin
    Zhu, Yanni
    Shi, Fei
    Yin, Hang
    Yu, Jie
    Huang, Pingjie
    Hou, Dibo
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 89 - 94
  • [3] A REVIEW OF VISION BASED DEFECT DETECTION USING IMAGE PROCESSING TECHNIQUES FOR BEVERAGE MANUFACTURING INDUSTRY
    Rahman, Nor Nabilah Syazana Abdul
    Saad, Norhashimah Mohd
    Abdullah, Abdul Rahim
    Ahmat, Norunnajjah
    JURNAL TEKNOLOGI, 2019, 81 (03): : 33 - 47
  • [4] A review on weed detection using ground-based machine vision and image processing techniques
    Wang, Aichen
    Zhang, Wen
    Wei, Xinhua
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2019, 158 : 226 - 240
  • [5] Image processing techniques in vision-based robot navigation
    Munguia, Rodrigo
    Bolea, Yolanda
    Grau, Antoni
    2018 INTERNATIONAL CONFERENCE ON CONTROL, ARTIFICIAL INTELLIGENCE, ROBOTICS & OPTIMIZATION (ICCAIRO), 2018, : 171 - 176
  • [6] Graph signal processing based underwater image enhancement techniques
    Sharma, Shobha
    Varma, Tarun
    ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH, 2022, 32
  • [7] AN ANALYSIS ON MACHINE VISION AND IMAGE PROCESSING TECHNIQUES FOR WEED DETECTION IN AGRICULTURAL CROPS
    Sohail, Rameen
    Nawaz, Qamar
    Hamid, Isma
    Gilani, Syed Mushhad Mustuzhar
    Mumtaz, Imran
    Mateen, Ahmad
    Chauhdary, Junaid Nawaz
    PAKISTAN JOURNAL OF AGRICULTURAL SCIENCES, 2021, 58 (01): : 187 - 204
  • [8] On the Effectiveness of Image Processing Based Malware Detection Techniques
    Bijitha, C., V
    Nath, Hiran, V
    CYBERNETICS AND SYSTEMS, 2022, 53 (07) : 615 - 640
  • [9] Computer Vision Technology for Fault Detection Systems Using Image Processing
    Alghawli, Abed Saif
    CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 73 (01): : 1961 - 1976
  • [10] Image pre-processing in computer vision systems for melanoma detection
    Vocaturo, Eugenio
    Zumpano, Ester
    Veltri, Pierangelo
    PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2018, : 2117 - 2124