opencv之膨脹與腐蝕
- 2019 年 10 月 14 日
- 筆記
腐蝕和膨脹 Erosion/Dilation
erosion/dilation,用白話說,就是讓圖像亮的區域收縮和擴張.
原理
- 我們定義一個卷積核矩陣.這個矩陣可以是任何形狀的,但通常而言,是矩形或者圓形的.同時要定義一個錨點位置.
- 用這個卷積核矩陣挨個地划過原始圖像矩陣,同時更改錨點位置的像素值.
- 錨點位置的像素值更改為卷積核矩陣覆蓋的有效像素值中的最大值/最小值(分別對應膨脹/腐蝕).
什麼叫"有效"像素值呢?就是卷積核中不為0的那些位置.用公式表達的話,即:
膨脹和腐蝕,說白了就是個求"卷積核所表示的局部"的最大值最小值的過程.
我們來看一個例子:
import cv2 import numpy as np def test1(): img = np.zeros((10,10,1),np.uint8) img[3:7,3:7,:] = 255 img[4:6,4:6,:] = 200 kernel1 = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3)) erosion_dst = cv2.erode(img, kernel1) print(erosion_dst)首先我們創建一個10 x 10的圖像,像素如下:
[[ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 255 255 255 255 0 0 0] [ 0 0 0 255 200 200 255 0 0 0] [ 0 0 0 255 200 200 255 0 0 0] [ 0 0 0 255 255 255 255 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0]]我們創建一個卷積核:
kernel1 = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3))getStructuringElement api
三個參數分別為卷積核的形狀/大小/錨點位置. 默認錨點在矩陣的中心位置.
形狀有三種
上面代碼中我們創建的3 x 3矩形卷積核如下
用這個卷積核對原始圖像做腐蝕後得到的矩陣如下
即矩陣有如下變化:
[[ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 255 255 255 255 0 0 0] [ 0 0 0 255 200 200 255 0 0 0] [ 0 0 0 255 200 200 255 0 0 0] [ 0 0 0 255 255 255 255 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0]] --> [[ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 200 200 0 0 0 0] [ 0 0 0 0 200 200 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0]]我們考慮第三行第四列img[2,3,:]這個像素.當我們的卷積核矩陣的錨點位置與該像素重合時,我們取周邊所有像素的最小值.最小值為0.所以該位置的像素值變為0. 其餘位置的像素值同理可求.
我們稍微改一下我們的代碼,然後再看一下不同卷積核作用下的不同結果,會理解的更清楚
import cv2 import numpy as np def test1(): img = np.zeros((10,10,1),np.uint8) img[3:7,3:7,:] = 255 img[4:6,4:6,:] = 200 kernel1 = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3)) print(kernel1) erosion_dst = cv2.erode(img, kernel1) print(erosion_dst) def test2(): img = np.zeros((10,10,1),np.uint8) img[3:7,3:7,:] = 255 img[4:6,4:6,:] = 200 img[2,4,:] = 100 kernel1 = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3)) erosion_dst = cv2.erode(img, kernel1) print(erosion_dst) kernel2 = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3)) erosion_dst2 = cv2.erode(img, kernel2) print(erosion_dst2) test2() 我們把原始圖像矩陣改為
[[ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 100 0 0 0 0 0] [ 0 0 0 255 255 255 255 0 0 0] [ 0 0 0 255 200 200 255 0 0 0] [ 0 0 0 255 200 200 255 0 0 0] [ 0 0 0 255 255 255 255 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0]]用kernal1時,kernal1如下:
以第四行,第五列的像素為例,用卷積核的錨點與之對應,此時計算的是其周圍八個像素的最小值,最小值為0.
所以我們得到的矩陣為
當我們用kernal2時,kernal2如下:
對第四行,第五列的像素,用卷積核的錨點與之對應,此時計算的不再是周圍八個像素的最小值,而是其正上方,正下方,正左邊,正右邊的四個像素的最小值.該值為100.
所以我們得到的矩陣為
opencv示例
from __future__ import print_function import cv2 as cv import numpy as np import argparse erosion_size = 0 max_elem = 2 max_kernel_size = 21 title_trackbar_element_type = 'Element:n 0: Rect n 1: Cross n 2: Ellipse' title_trackbar_kernel_size = 'Kernel size:n 2n +1' title_erosion_window = 'Erosion Demo' title_dilatation_window = 'Dilation Demo' def erosion(val): erosion_size = cv.getTrackbarPos(title_trackbar_kernel_size, title_erosion_window) erosion_type = 0 val_type = cv.getTrackbarPos(title_trackbar_element_type, title_erosion_window) if val_type == 0: erosion_type = cv.MORPH_RECT elif val_type == 1: erosion_type = cv.MORPH_CROSS elif val_type == 2: erosion_type = cv.MORPH_ELLIPSE element = cv.getStructuringElement(erosion_type, (2*erosion_size + 1, 2*erosion_size+1), (erosion_size, erosion_size)) erosion_dst = cv.erode(src, element) cv.imshow(title_erosion_window, erosion_dst) def dilatation(val): dilatation_size = cv.getTrackbarPos(title_trackbar_kernel_size, title_dilatation_window) dilatation_type = 0 val_type = cv.getTrackbarPos(title_trackbar_element_type, title_dilatation_window) if val_type == 0: dilatation_type = cv.MORPH_RECT elif val_type == 1: dilatation_type = cv.MORPH_CROSS elif val_type == 2: dilatation_type = cv.MORPH_ELLIPSE element = cv.getStructuringElement(dilatation_type, (2*dilatation_size + 1, 2*dilatation_size+1), (dilatation_size, dilatation_size)) dilatation_dst = cv.dilate(src, element) cv.imshow(title_dilatation_window, dilatation_dst) src = cv.imread("/home/sc/disk/keepgoing/opencv_test/j.png") cv.namedWindow(title_erosion_window) cv.createTrackbar(title_trackbar_element_type, title_erosion_window , 0, max_elem, erosion) cv.createTrackbar(title_trackbar_kernel_size, title_erosion_window , 0, max_kernel_size, erosion) cv.namedWindow(title_dilatation_window) cv.createTrackbar(title_trackbar_element_type, title_dilatation_window , 0, max_elem, dilatation) cv.createTrackbar(title_trackbar_kernel_size, title_dilatation_window , 0, max_kernel_size, dilatation) erosion(0) dilatation(0) cv.waitKey()通過createTrackbar在窗口上創建兩個bar,方便我們看不同種類不同大小的卷積核的影響.
cv.createTrackbar(title_trackbar_element_type, title_erosion_window , 0, max_elem, erosion) cv.createTrackbar(title_trackbar_kernel_size, title_erosion_window , 0, max_kernel_size, erosion)原始圖片:
處理效果:
