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In this paper, an automatic oral liquid light inspection algorithm is designed to implement the detection
of particles in oral liquid. Second-difference and accumulate difference methods are used to remove the background
information the sequence images captured by a high-speed industry camera, and the target images with particles,
air bubble and random noise are acquired. Adaptive threshold processing is used to extract moving targets.
Real-time detection is completed by determining whether the size of particles, such as hair, fibers and so on, is larger
than the pharmaceutical standards. A large number of experimental results show that the proposed algorithm is
effective and feasible-In this paper, an automatic oral liquid light inspection algorithm is designed to implement the detection
of particles in oral liquid. Second-difference and accumulate difference methods are used to remove the background
information the sequence images captured by a high-speed industry camera, and the target images with particles,
air bubble and random noise are acquired. Adaptive threshold processing is used to extract moving targets.
Real-time detection is completed by determining whether the size of particles, such as hair, fibers and so on, is larger
than the pharmaceutical standards. A large number of experimental results show that the proposed algorithm is
effective and feasible
of particles in oral liquid. Second-difference and accumulate difference methods are used to remove the background
information the sequence images captured by a high-speed industry camera, and the target images with particles,
air bubble and random noise are acquired. Adaptive threshold processing is used to extract moving targets.
Real-time detection is completed by determining whether the size of particles, such as hair, fibers and so on, is larger
than the pharmaceutical standards. A large number of experimental results show that the proposed algorithm is
effective and feasible-In this paper, an automatic oral liquid light inspection algorithm is designed to implement the detection
of particles in oral liquid. Second-difference and accumulate difference methods are used to remove the background
information the sequence images captured by a high-speed industry camera, and the target images with particles,
air bubble and random noise are acquired. Adaptive threshold processing is used to extract moving targets.
Real-time detection is completed by determining whether the size of particles, such as hair, fibers and so on, is larger
than the pharmaceutical standards. A large number of experimental results show that the proposed algorithm is
effective and feasible
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iData_基于图像处理的大输液中可见异物检测方法研究_王美珍.caj
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