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Fusing Data Processing in the Construction of Machine Vision Systems in Robotic Complexes

机译:机器人复合体机器视觉系统构建中的融合数据处理

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The development of machine vision systems is based on the analysis of visual information recorded by sensitive matrices. This information is most often distorted by the presence of interfering factors represented by a noise component. The common causes of the noise include imperfect sensors, dust and aerosols, used ADCs, electromagnetic interference, and others. The presence of these noise components reduces the quality of the subsequent analysis. To implement systems that allow operating in the presence of a noise, a new approach, which allows parallel processing of data obtained in various electromagnetic ranges, has been proposed. The primary area of application of the approach are machine vision systems used in complex robotic cells. The use of additional data obtained by a group of sensors allows the formation of arrays of usefull information that provide successfull optimization of operations. The set of test data shows the applicability of the proposed approach to combined images in machine vision systems.
机译:机器视觉系统的开发基于对敏感矩阵记录的视觉信息的分析。该信息最常因存在以噪声分量表示的干扰因素而失真。造成噪声的常见原因包括传感器不完善,灰尘和气溶胶,使用过的ADC,电磁干扰等。这些噪声成分的存在降低了后续分析的质量。为了实现允许在噪声存在下运行的系统,已经提出了一种新方法,该方法允许并行处理在各种电磁范围内获得的数据。该方法的主要应用领域是复杂机器人单元中使用的机器视觉系统。由一组传感器获得的附加数据的使用允许形成有用信息的阵列,这些信息可提供对操作的成功优化。测试数据集显示了所提出的方法在机器视觉系统中对组合图像的适用性。

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