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Airport Signs and Markings Recognition for Enhanced Runway Incursion Avoidance
| Content Provider | Semantic Scholar |
|---|---|
| Author | Wang, Huafei |
| Copyright Year | 2015 |
| Abstract | Detecting and recognizing runway holding position signs and hold-short lines are of significant safety interest for runway incursion avoidance. It is an important supplement to pilots’ education and airport ground radar to enhance safety, particularly at complex major airports. In this project, we leverage the standards of airport signs and markings for the detection and recognition purposes. For sign detection and recognition, an HSV color space based algorithm is developed to detect runway holding positions signs and Optical Character Recognition (OCR) is used to recognized the signs. For line detection, Canny Edge Detection and Hough Transform are used to recognize major line features in the images, and a heuristic algorithm leveraging the layout characteristics of the images is used to determine the presence of hold-short lines among those lines. An accuracy of 95.1% is achieved for runway holding position signs detection and recognition while an accuracy of 89.2% is achieved for runway hold-short line detection. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://web.stanford.edu/class/ee368/Project_Spring_1415/Reports/Wang_Wang.pdf |
| Alternate Webpage(s) | http://web.stanford.edu/class/ee368/Project_Spring_1415/Posters/Wang_Wang.pdf |
| Alternate Webpage(s) | http://web.stanford.edu/class/ee368/Project_Spring_1415/Reports/Wang_Wang.pdf |
| Alternate Webpage(s) | https://web.stanford.edu/class/ee368/Project_Spring_1415/Proposals/Wang_Wang.pdf |
| Alternate Webpage(s) | http://web.stanford.edu/class/ee368/Project_Spring_1415/Proposals/Wang_Wang.pdf |
| Alternate Webpage(s) | https://web.stanford.edu/class/ee368/Project_Spring_1415/Posters/Wang_Wang.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
