opencv之膨胀与腐蚀
- 2019 年 10 月 14 日
- 筆記
腐蚀和膨胀 Erosion/Dilation
erosion/dilation,用白话说,就是让图像亮的区域收缩和扩张.
原理
- 我们定义一个卷积核矩阵.这个矩阵可以是任何形状的,但通常而言,是矩形或者圆形的.同时要定义一个锚点位置.
- 用这个卷积核矩阵挨个地划过原始图像矩阵,同时更改锚点位置的像素值.
- 锚点位置的像素值更改为卷积核矩阵覆盖的有效像素值中的最大值/最小值(分别对应膨胀/腐蚀).
什么叫"有效"像素值呢?就是卷积核中不为0的那些位置.用公式表达的话,即:
膨胀和腐蚀,说白了就是个求"卷积核所表示的局部"的最大值最小值的过程.
我们来看一个例子:
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)首先我们创建一个10 x 10的图像,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]]我们创建一个卷积核:
kernel1 = cv2.getStructuringElement(cv2.MORPH_RECT,(3,3))getStructuringElement api
三个参数分别为卷积核的形状/大小/锚点位置. 默认锚点在矩阵的中心位置.
形状有三种
上面代码中我们创建的3 x 3矩形卷积核如下
用这个卷积核对原始图像做腐蚀后得到的矩阵如下
即矩阵有如下变化:
[[ 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]]我们考虑第三行第四列img[2,3,:]这个像素.当我们的卷积核矩阵的锚点位置与该像素重合时,我们取周边所有像素的最小值.最小值为0.所以该位置的像素值变为0. 其余位置的像素值同理可求.
我们稍微改一下我们的代码,然后再看一下不同卷积核作用下的不同结果,会理解的更清楚
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() 我们把原始图像矩阵改为
[[ 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时,kernal1如下:
以第四行,第五列的像素为例,用卷积核的锚点与之对应,此时计算的是其周围八个像素的最小值,最小值为0.
所以我们得到的矩阵为
当我们用kernal2时,kernal2如下:
对第四行,第五列的像素,用卷积核的锚点与之对应,此时计算的不再是周围八个像素的最小值,而是其正上方,正下方,正左边,正右边的四个像素的最小值.该值为100.
所以我们得到的矩阵为
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()通过createTrackbar在窗口上创建两个bar,方便我们看不同种类不同大小的卷积核的影响.
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)原始图片:
处理效果:
