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Development of Computer Vision-Enhanced Smart Golf Ball Retriever

Lee Shun-Liang Lin Pang-Chieh Lin Sheng-Jie Kung Huang-Kuang 関西大学

2020.03.20

概要

An automatic vehicle system was developed to assist golfers in collecting golf balls from a practice field. Computer vision methodology was utilized to enhance the detection of golf balls in shallow and/or deep grass regions. The free software OpenCV was used in this project because of its powerful features and supported repository.

The homemade golf ball picker was built with a smart recognition function for golf balls and can lock onto targets by itself. A set of field tests was completed in which the rate of golf ball recognition was as high as 95%. We report that this homemade smart golf ball picker can reduce the tremendous amount of labor associated with having to gather golf balls scattered throughout a practice field.

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参考文献

[1]Installing OpenCV 3 With Python On Mac OS X, https://prateekvjoshi.com/2015/10/09/installing-OpenCV-3-with-Python-on-mac-os-x/

[2]16 OpenCV Functions to Start your Computer Vision journey (with Python code), https://www.analyticsvidhya.com/blog/2019/03/OpenCV-functions-computer-vision-Python/

[3]Color Detection in Python with OpenCV, https://henrydangprg.com/2016/06/26/color-detection-in-Python-with-OpenCV/

[4]OpenCV-Python Tutorials:Image Gradients, https://OpenCV-Python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_ gradients/py_gradients.html

[5]OpenCV-Python Tutorials:Canny Edge Detection, https://OpenCV-Python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_canny/ py_canny.html

[6]Learning OpenCV3 computer vision with Python (second edition), Joe Minichino and Joseph Howse, PACKT publishing.

[7]Programming computer vision with Python, JanErik Solen, O'REILLY publishing.

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