python中用区域掩模实现车道线检测

1.颜色阈值+ 区域掩模

我们可以仅仅通过设置一些RGB通道阈值，来提取车道线。

以下的代码设置了RGB通道阈值为220，大于220的像素将设置为黑色，这样可以将测试图片中的车道线提取出来

效果如下

我们发现符合阈值的像素既包括了车道线，也包含了其他非车道线部分。

显然，一个成熟的自动驾驶感知算法，是不可能使用这种方法的。仅仅依靠颜色，既不科学也不鲁棒。

有一种改进思路是利用图像掩模的方法

假设拍摄图像的前置摄像头安装在汽车上的固定位置，这样车道线将始终出现在图像的相同区域中。我们将设置了一个区域，认为车道线处于该区域内。

我们设置了一个三角形的区域，原则上你可以使用其他形状

![图

python代码如下

import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np


# Read in the image
image = mpimg.imread('test.jpg')


# Grab the x and y sizes and make two copies of the image
# With one copy we'll extract only the pixels that meet our selection,
# then we'll paint those pixels red in the original image to see our selection
# overlaid on the original.
ysize = image.shape[0]
xsize = image.shape[1]
color_select= np.copy(image)
line_image = np.copy(image)


# Define our color criteria
red_threshold = 220
green_threshold = 220
blue_threshold = 220
rgb_threshold = [red_threshold, green_threshold, blue_threshold]


# Define a triangle region of interest (Note: if you run this code,
left_bottom = [0, ysize-1]
right_bottom = [xsize-1, ysize-1]
apex = [650, 400]


fit_left = np.polyfit((left_bottom[0], apex[0]), (left_bottom[1], apex[1]), 1)
fit_right = np.polyfit((right_bottom[0], apex[0]), (right_bottom[1], apex[1]), 1)
fit_bottom = np.polyfit((left_bottom[0], right_bottom[0]), (left_bottom[1], right_bottom[1]), 1)


# Mask pixels below the threshold
color_thresholds = (image[:,:,0] < rgb_threshold[0]) | 
                    (image[:,:,1] < rgb_threshold[1]) | 
                    (image[:,:,2] < rgb_threshold[2])


# Find the region inside the lines
XX, YY = np.meshgrid(np.arange(0, xsize), np.arange(0, ysize))
region_thresholds = (YY > (XX*fit_left[0] + fit_left[1])) & 
                    (YY > (XX*fit_right[0] + fit_right[1])) & 
                    (YY < (XX*fit_bottom[0] + fit_bottom[1]))
# Mask color selection
color_select[color_thresholds] = [0,0,0]
# Find where image is both colored right and in the region
line_image[~color_thresholds & region_thresholds] = [255,0,0]


# Display our two output images
plt.imshow(color_select)
plt.imshow(line_image)


# uncomment if plot does not display
plt.show()