Title :
Runway detection using line segment statistical model
Author :
Cao, Shixiang ; Jiang, Jie ; Zhang, Guangjun ; Yuan, Yan
Author_Institution :
Key Lab. for Precision Opto-Mechatron. Technol., Beihang Univ., Beijing, China
Abstract :
To meet the needs of precise runway detection in remote sensing images, while reducing unnecessary adjustable parameters, an efficient and parameter free method is proposed to extract the straight edge of runway based on Helmholtz principle. By introducing the model of line segment model, we compute and analyze the gradient of the pixels on a given oriented line, and then the problem of line segment is classified into hypothesis test under tolerant significance. In theory, this proposed method can limit the number of false alarms and turns out to be parameterless. Using the end point of detected line segment, the extraction of parallel line is of light computational burden. The results of concrete surface and pitch surface airport show our method avoid initializing the type of runway, and is not sensitive to noise and the gray-level difference between airport and ground. The final allocation of runway in an image is accurate and the turning around time is greatly condensed.
Keywords :
edge detection; feature extraction; remote sensing; statistical analysis; Helmholtz principle; concrete surface airport; false alarms; feature extraction; gray level difference; hypothesis test; line segment detection; line segment model; line segment statistical model; pitch surface airport; remote sensing images; runway detection; Airports; Educational institutions; Image edge detection; Image segmentation; Noise; Remote sensing; Standards;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2012 Third International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4577-2144-1
DOI :
10.1109/ICICIP.2012.6391420