Study on Image Detection Method of Navigation Route for Cotton Harvester


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This paper presents an image detection algorithm for navigation route of cotton harvester. Two cameras were respectively installed on the leftmost and rightmost picker unit, and images were captured during working process respectively. Firstly, the color characteristics among harvested field, un-harvested field, outside-field and the end of field were analyzed, then the target features of different fields was extracted using the color difference 3B-R-G. Secondly, candidate point group was determined by looking for the critical point of peak from the lowest trough point to un-harvested field and associating with the detection result of the anterior frame. Lastly, navigation line was obtained by using passing a Known Point Hough Transform (PKPHT). Results show that the navigation line detected using this algorithm can fit the boundary line and the edge of field accurately, the average processing time is56.10ms/f, and the algorithm can meet the actual production needs of cotton harvester.



Edited by:

Fangyin Cheng and Yan Ma




J. B. Li et al., "Study on Image Detection Method of Navigation Route for Cotton Harvester", Applied Mechanics and Materials, Vols. 246-247, pp. 219-224, 2013

Online since:

December 2012




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