已知植物位置的作物行检测 - 如何？
Crop-row detection of already known plant positions - How to?
通过图像识别和分割，我已经获得了田野上植物的抽象表示（即我确切地知道图像中所有植物的所有坐标）。
现在我想检测这个抽象表示中的作物行 - 但不太清楚如何做。
我的问题是：
- 图像中的行可能有点旋转，而不是完全 north/south 方向（角度可能在 -10° 到 +10° 之间变化）
- 每幅图像的裁剪行数可能因图像而异且不固定 - 在处理发生之前也是未知的
- 每张处理过的图像中裁剪行的旋转可能略有不同
- 我有数百个图像/表示要处理（所以手工处理显然不太可行:-)），所以我需要一个算法，我可以稍后使用，例如放入循环
你能不能帮我至少一个策略（或代码片段）来做这样的裁剪行检测？理想情况下，对于每一行作物，我最终都会有一个线性方程 (y=m*x+t) 的参数，这样就可以使用 abline()，但我对任何事情都持开放态度。最后它可能看起来像这样（这里纯粹是为了手工完成的说明目的）：
图像的基础数据在这里：
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172.129, 173.754, 191.456, 194.795, 98.098, 99.4479999999999,
62.1419999999998), .Dim = c(224L, 2L))
以下内容可能会有所帮助：
对于每个检测到的植物点，找到最近的相邻植物。希望这能更频繁地在同一作物行中找到植物。如果先验地知道图像大致在 north/south 方向，我们应该更喜欢在垂直方向上看更多来选择相邻的植物。一种方法是将最近邻搜索的“距离”重新定义为各向异性，例如
distance = 10 * (x0 - x1)² + (y0 - y1)²
下面是它产生的图，在每株植物和它最近的邻居之间画一条线段：
它并不完美，但可能是一个有用的开始。大多数作物行足够幸运，4 种或更多植物的 运行 被正确地链接在一起。
从这里思考一个可能的策略：
确定连接的组件，即植物的“链条”。
对于每个链，通过最小二乘法回归最佳拟合线。或者更好的是，使用 RANSAC algorithm 以便拟合稳健地忽略在其他共线链中的单个杂散植物。
再次使用粗略的 north/south 方向，只有当它足够接近垂直时才考虑最佳拟合线“有效”。假设它是有效的，找到所有接近最佳拟合线的植物。如果附近有许多植物，则最适合的线可能是作物行。
通过图像识别和分割，我已经获得了田野上植物的抽象表示（即我确切地知道图像中所有植物的所有坐标）。
现在我想检测这个抽象表示中的作物行 - 但不太清楚如何做。 我的问题是：
- 图像中的行可能有点旋转，而不是完全 north/south 方向（角度可能在 -10° 到 +10° 之间变化）
- 每幅图像的裁剪行数可能因图像而异且不固定 - 在处理发生之前也是未知的
- 每张处理过的图像中裁剪行的旋转可能略有不同
- 我有数百个图像/表示要处理（所以手工处理显然不太可行:-)），所以我需要一个算法，我可以稍后使用，例如放入循环
你能不能帮我至少一个策略（或代码片段）来做这样的裁剪行检测？理想情况下，对于每一行作物，我最终都会有一个线性方程 (y=m*x+t) 的参数，这样就可以使用 abline()，但我对任何事情都持开放态度。最后它可能看起来像这样（这里纯粹是为了手工完成的说明目的）：
图像的基础数据在这里：
structure(c(5278.072, 2632.564, 393.34, 4057.704, 3805.599, 611.269,
1823.835, 3359.069, 3598.284, 5262.873, 2069.963, 1579.745, 4539.584,
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172.129, 173.754, 191.456, 194.795, 98.098, 99.4479999999999,
62.1419999999998), .Dim = c(224L, 2L))
以下内容可能会有所帮助：
对于每个检测到的植物点，找到最近的相邻植物。希望这能更频繁地在同一作物行中找到植物。如果先验地知道图像大致在 north/south 方向，我们应该更喜欢在垂直方向上看更多来选择相邻的植物。一种方法是将最近邻搜索的“距离”重新定义为各向异性，例如
distance = 10 * (x0 - x1)² + (y0 - y1)²
下面是它产生的图，在每株植物和它最近的邻居之间画一条线段：
它并不完美，但可能是一个有用的开始。大多数作物行足够幸运，4 种或更多植物的 运行 被正确地链接在一起。
从这里思考一个可能的策略：
确定连接的组件，即植物的“链条”。
对于每个链，通过最小二乘法回归最佳拟合线。或者更好的是，使用 RANSAC algorithm 以便拟合稳健地忽略在其他共线链中的单个杂散植物。
再次使用粗略的 north/south 方向，只有当它足够接近垂直时才考虑最佳拟合线“有效”。假设它是有效的，找到所有接近最佳拟合线的植物。如果附近有许多植物，则最适合的线可能是作物行。