An artificial target location method for Curiosity rover

Ying Li; Jing Peng; Ying Du

doi:10.1117/12.2178743

4 March 2015 An artificial target location method for Curiosity rover

Ying Li, Jing Peng, Ying Du

Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94432R (2015) https://doi.org/10.1117/12.2178743
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China

Abstract

Template matching is a common method for object recognition and location. But the premise of template matching is the target should not change a lot in shape from the template image. When non-coplanar rotation exits, the traditional template matching method is helpless. By analyzing the artificial target of the curiosity rover, a two-step artificial target location method is proposed. Firstly, least squares ellipse fitting method is used to recognize the artificial target in the image and locate the center of each ellipse preliminary. Secondly, according to the preliminary result of ellipse fitting, the image is graph cut into pieces, and each piece only has one ellipse. Then Hough transform is used to locate the center of the artificial target precisely. Meanwhile, before edge detection, mathematical morphology technology is conducted to remove the influence of the shadow in the image. Otsu algorithm is used to choose the threshold value of canny edge detector adaptively. Experiments are carried out based on artificial target images of curiosity rover, which show that the robustness of the algorithm in non-ideal illumination situation. The location accuracy is within 1 pixel.

Citation Download Citation

Ying Li, Jing Peng, and Ying Du "An artificial target location method for Curiosity rover", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94432R (4 March 2015); https://doi.org/10.1117/12.2178743

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KEYWORDS

Detection and tracking algorithms

Edge detection

Hough transforms

Target recognition

Binary data

Sensors

Target detection

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