MEMS装配显微图像分割与特征点提取

Segmentation and Features Identification for MEMS Assembly Images under Microscope

  • 摘要: 介绍了MEMS装配显微图像的特点,并根据其在显微镜视野内啮合装配的特点和要求,通过将图像在不同方向上投影,从复杂背景中分割出目标图像的轮廓区域.进一步分析齿轮的颜色构成特点,采用HSV颜色感知模型和R-B模型,在齿轮轮廓区域内提取清晰齿轮二值图像.根据齿轮齿间间距,将齿轮二值图像分成 12等份,在轮廓区域内搜索齿轮外齿廓,寻找齿轮的特征点,为微型行星齿轮减速器的抓取、啮合装配提供位置信息.

     

    Abstract: The assembly of the micro planetary gears under microscope, 400μm in diameter, is introduced briefly. To segment the outline of the target gear from the terribly degraded source image, images captured under microscope are projected into lines with different slope angles. However, the profile lacks details and important features for image understanding and object recognition but extremely decreasing the computing complexity. HSV (Hue Saturation Value) model and R-B model are applied to the analysis of the details and important features of the target. Then, based on the result of the HSV model and R-B model, target image is divided into 12 parts, and one of the gear profile is searched according to its diameter passing center point, which will offer location to the micro manipulating robot.

     

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