Reverse rasterizing is referred to as vectorizing. The algorithms are generally quite complex, here's a googlet of a few of them. Check out sparse pixel tracking and sparse pixel vectorization for some good examples.
For good algorithms for polygon partitioning, check out Joespeh O'Rourkes 'Computational Geometry in C', ISBN 0-521-44034-3, or search for concave polygon partitioning algorithms, such as this
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反向光栅化称为矢量化。 这些算法通常相当复杂，这里有一个 googlet 其中一些。 查看稀疏像素跟踪和稀疏像素矢量化以获得一些很好的示例。
有关多边形分区的良好算法，请查看 Joespeh O'Rourkes 'C 中的计算几何'，ISBN 0-521-44034-3，或搜索 凹多边形分区算法，例如这个
Reverse rasterizing is referred to as vectorizing. The algorithms are generally quite complex, here's a googlet of a few of them. Check out sparse pixel tracking and sparse pixel vectorization for some good examples.
For good algorithms for polygon partitioning, check out Joespeh O'Rourkes 'Computational Geometry in C', ISBN 0-521-44034-3, or search for concave polygon partitioning algorithms, such as this
这在 GIS 中很常见 - 例如，从航空摄影中自动提取特征。 选择的开源工具是：
链接 链接
链接
This is quite common in GIS - e.g. extracting features automatically from aerial photography. The OpenSource tool of choice would be:
Link
Link
我通过 Python 接口使用 OpenCV 的
findContours方法：https://opencv-python- tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_contours/py_contours_begin/py_contours_begin.html
I am using OpenCV's
findContoursmethod through their Python interface:https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_contours/py_contours_begin/py_contours_begin.html