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An efficient edge detection algorithm for 2D-3D conversion

机译:用于2D-3D转换的有效边缘检测算法

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摘要

The 2D-3D conversion requires 2D content to convert into 3D display. This conversion process first estimates the 3D structure of the scene and then rendered the scene; finally it produces 3D images. In Existing system, the Hybrid depth generation algorithm has three depth cues for depth estimation: motion information, linear perspective, and texture characteristics. To find the edge detection they are using a sobel operator. We propose a canny edge detection algorithm instead of sobel operator to find the accurate edge detection; this edge detection algorithm is used to reduce the amount of data in the image. This approach used to detect the real edge points and non edge points. It should maximize the real edge points and minimize the non edge points. These similarities to maximize the signal to noise ratio. The detected edges as close as to the real edges. The real edge should not result as the detected edge. Using a canny edge detection algorithm the visual perception of the image can be improved.
机译:2D-3D转换需要2D内容才能转换为3D显示。此转换过程首先估计场景的3D结构,然后渲染场景;然后,进行渲染。最终生成3D图像。在现有系统中,混合深度生成算法具有用于深度估计的三个深度提示:运动信息,线性透视图和纹理特征。为了找到边缘检测,他们使用了sobel运算符。我们提出了一种精巧的边缘检测算法,而不是sobel算子,以找到准确的边缘检测。该边缘检测算法用于减少图像中的数据量。该方法用于检测实际边缘点和非边缘点。它应该最大化实际边缘点,并最小化非边缘点。这些相似之处使信噪比最大化。检测到的边缘与真实边缘尽可能接近。实际边缘不应作为检测到的边缘。使用Canny边缘检测算法,可以改善图像的视觉感知。

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