1.顏色閾值+ 區域掩模

我們可以僅僅通過設置一些RGB通道閾值，來提取車道線。

以下的代碼設置了RGB通道閾值為220，大于220的像素將設置為黑色，這樣可以將測試圖片中的車道線提取出來

效果如下

我們發現符合閾值的像素既包括了車道線，也包含了其他非車道線部分。

顯然，一個成熟的自動駕駛感知算法，是不可能使用這種方法的。僅僅依靠顏色，既不科學也不魯棒。

有一種改進思路是利用圖像掩模的方法

假設拍攝圖像的前置攝像頭安裝在汽車上的固定位置，這樣車道線將始終出現在圖像的相同區域中。我們將設置了一個區域，認為車道線處于該區域內。

我們設置了一個三角形的區域，原則上你可以使用其他形狀

![圖

python代碼如下

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()