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홍형길(Hyunggil Hong),장선호(Sunho Jang),조용준(Yongjun Cho),윤해룡(Haeyong Yun),송재욱(Jae Wook Song) 한국기계가공학회 2023 한국기계가공학회지 Vol.22 No.7
A horticultural robotic system was designed to address the problems caused by the increased cost of agricultural materials, pesticide poisoning, and soil pollution due to the excessive use of pesticides. The system consists of a crop recognition module, remote control, sprayer system, and an integrated control module. First, the system communicates the speed and status of the platform to the integrated control module. Second, the crop recognition module transmits the crop recognition results to the spray system based on images acquired by the cameras on the left and right sides of the platform. Third, the system recognizes and sprays the pesticide onto the target crops according to the platform speed. Finally, seven factors (i.e., crop detection rate, gradient, straight forwardness, obstacle-overcoming step, road speed, spraying efficiency, and pesticide consumption) were evaluated to ensure that the correct pesticide spraying operation is performed while maintaining a stable position.
A reliable quasi-dense corresponding points for structure from motion
( Jangseok Oh ),( Hyunggil Hong ),( Yongjun Cho ),( Haeyong Yun ),( Kap-ho Seo ),( Hochul Kim ),( Mingi Kim ),( Onseok Lee ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.9
A three-dimensional (3D) reconstruction is an important research area in computer vision. The ability to detect and match features across multiple views of a scene is a critical initial step. The tracking matrix W obtained from a 3D reconstruction can be applied to structure from motion (SFM) algorithms for 3D modeling. We often fail to generate an acceptable number of features when processing face or medical images because such images typically contain large homogeneous regions with minimal variation in intensity. In this study, we seek to locate sufficient matching points not only in general images but also in face and medical images, where it is difficult to determine the feature points. The algorithm is implemented on an adaptive threshold value, a scale invariant feature transform (SIFT), affine SIFT, speeded up robust features (SURF), and affine SURF. By applying the algorithm to face and general images and studying the geometric errors, we can achieve quasi-dense matching points that satisfy well-functioning geometric constraints. We also demonstrate a 3D reconstruction with a respectable performance by applying a column space fitting algorithm, which is an SFM algorithm.