Row-detection on an agricultural field using omnidirectional camera

This paper describes a method of detecting parallel rows on an agricultural field using an omnidirectional camera. The method works both on cameras with a fisheye lens and cameras with a catadioptric lens. A combination of an edge based method and a Hough transform method is suggested to find the rows. The vanishing point of several parallel rows is estimated using a second Hough transform. The method is evaluated on synthetic images generated with calibration data from real lenses. Scenes with several rows are produced, where each plant is positioned with a specified error. Experiments are performed on these synthetic images and on real field images. The result shows that good accuracy is obtained on the vanishing point once it is detected correctly. Further it shows that the edge based method works best when the rows consists of solid lines, and the Hough method works best when the rows consists of individual plants. The experiments also show that the combined method provides better detection than using the methods separately.