首页> 外文会议>Image Analysis and Interpretation, 1994., Proceedings of the IEEE Southwest Symposium on >Subpixel edge estimation using geometrical edge models with noise miniaturization
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Subpixel edge estimation using geometrical edge models with noise miniaturization

机译:使用具有噪声最小化的几何边缘模型进行亚像素边缘估计

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The significant disadvantage for traditional contour representation is as the resolution is reduced the effort of undersampling is proportional enlarged. The goal of this study is to improve edge detection results, especially for those corner points in low resolution. This study describes a method, which is based on 4-connected pixel-wise linearization, for finding contours from low resolution video images. This allows a more accurate inspection and identification of objects from image data. In practice, geometrical models are used to manipulate this linearization. A method is employed for examining the corner points as well.
机译:传统轮廓表示法的主要缺点是,随着分辨率的降低,欠采样的工作量成比例增加。这项研究的目的是改善边缘检测结果,尤其是对于那些低分辨率的拐角点。这项研究描述了一种基于4像素像素线性化的方法,用于从低分辨率视频图像中查找轮廓。这允许从图像数据中更准确地检查和识别对象。在实践中,使用几何模型来操纵此线性化。还采用一种方法来检查拐角点。

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