Abstract
This paper proposes a fish contour detection method using a local kernel regression method. To do this task, the followings are done. Firstly, 3D depth map of a fish is obtained by using Kinect camera sensor. Secondly, edge of the fish in 3D depth map is transformed into numerous points. Thirdly, all information is removed except the edge points. However, recognition points for recognizing the fish are appropriately left because there are only points left to distinguish between background and fish. Fourthly, the points are recognized as contour of the fish by using the local kernel regression method. Finally, experiment results using Kinect camera sensor are shown to verify the validity of the proposed method compared to Canny method.
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Acknowledgments
This research was a part of the project titled “Localization of unloading automation system related to Korean type of fish pump (20150446)”, funded by the Ministry of Oceans and Fisheries, Korea.
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Oh, J.M. et al. (2020). Contour Detection Method of 3D Fish Using a Local Kernel Regression Method. In: Zelinka, I., Brandstetter, P., Trong Dao, T., Hoang Duy, V., Kim, S. (eds) AETA 2018 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application. AETA 2018. Lecture Notes in Electrical Engineering, vol 554. Springer, Cham. https://doi.org/10.1007/978-3-030-14907-9_93
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DOI: https://doi.org/10.1007/978-3-030-14907-9_93
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