fanfuhan OpenCV 教學066 ~ opencv-066-圖像形態學(開閉操作時候結構元素應用演示) – jashliao部落格

fanfuhan OpenCV 教學066 ~ opencv-066-圖像形態學(開閉操作時候結構元素應用演示)

資料來源: https://fanfuhan.github.io/

https://fanfuhan.github.io/2019/04/20/opencv-066/

GITHUB:https://github.com/jash-git/fanfuhan_ML_OpenCV

OpenCV中圖像形態學開操作與閉操作，根據結構元素的不同可以實現不同的二值圖像處理效果，我們可以通過下面的結構元素對圖像進行開操作，提取二值圖像中水平與垂直線，這個方法比霍夫直線檢測要好用得多， 在一些應用場景中會特別有用，圖像分析、OCR佈局分析中形態學操作十分重要，我們通過兩個例子來說明開閉操作的作用。

1開操作提取水平線，實現填空題橫線位置提取
結構元素大小為20×1
    步驟：
        01.轉灰度
        02.轉二值，可選降噪
        03.形態學操作，提取(偵測/尋找/檢測)水平線
        04.輪廓發現，確定位置

2閉操作實現不同層次的輪廓填充
    結構元素分為三種：
        矩形結構元素35×35大小
        矩形結構元素30×30大小
        圓形結構元素30×30大小

C++

#include  
#include  

using  namespace  std ; 
using  namespace cv;

void  open_demo () ;
void  close_demo () ;

/* 
*圖像形態學(開閉操作時候結構元素應用演示) 
*/ 
int  main ()  
{ 
	//open_demo();
	close_demo();
    waitKey( 0 );
	return 0 ; 
}

void close_demo ()  
{
	//讀取圖像     
	Mat src = imread( "../images/morph3.png" );
    imshow( "input" , src);
    
    //二值圖像
    Mat gray, binary; 
    cvtColor(src, gray, COLOR_BGR2GRAY); 
    threshold(gray, binary, 0 , 255 , THRESH_BINARY | THRESH_OTSU); 
    imshow( "binary" , binary);

    //閉操作//
	Mat se = getStructuringElement(MORPH_ELLIPSE, Size(30, 30), Point(-1, -1)); 
	//Mat se = getStructuringElement(MORPH_RECT, Size(30, 30), Point(-1 , -1));
	//Mat se = getStructuringElement(MORPH_RECT, Size( 35 , 35 ), Point( -1 , -1 ));
	morphologyEx(binary, binary, MORPH_CLOSE, se);
	imshow( "close_demo rect=35,35 " , binary); 
}

void open_demo ()  
{ 
	//讀取圖像     
	Mat src = imread( "../images/fill.png" );    
	imshow( "input" , src);
    
    //二值圖像
    Mat gray, binary; 
    cvtColor(src, gray, COLOR_BGR2GRAY); 
    threshold(gray, binary, 0 , 255 , THRESH_BINARY_INV | THRESH_OTSU); 
    imshow( "binary" , binary);

    //開操作
    Mat se = getStructuringElement(MORPH_RECT, Size( 25 , 1 ), Point( -1 , -1 )); 
    morphologyEx(binary, binary, MORPH_OPEN, se); 
    imshow( "open_op" , binary);

    //繪製填空位置
	vector < vector > contours;
	vector  hierarhy;
	findContours(binary, contours, hierarhy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point( -1 , -1 ));
	for ( size_t t = 0 ; t < contours.size(); t++)
	{
		Rect roi = boundingRect(contours[t]);         
		roi.y = roi.y - 10 ;         
		roi.height = 12 ;         
		rectangle(src, roi, Scalar( 0 , 0 , 255 ));
	}

    //顯示結果
    imshow( "open_demo" , src); 
}

Python

import cv2 as cv 
import numpy as np


def  open_demo () :
    src = cv.imread( "D:/images/fill.png" )
    cv.namedWindow( "input" , cv.WINDOW_AUTOSIZE)
    cv.imshow( "input" , src)

    #圖像二值化
     gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY) 
    ret, binary = cv.threshold(gray, 0 , 255 , cv.THRESH_BINARY_INV | cv.THRESH_OTSU) 
    cv.imwrite( "D:/binary1.png " , binary) 
    cv.imshow( "binary1" , binary)

    #開操作
    se1 = cv.getStructuringElement(cv.MORPH_RECT, ( 20 , 1 ), ( -1 , -1 )) 
    binary = cv.morphologyEx(binary, cv.MORPH_OPEN, se1) 
    cv.imshow( "binary" , binary ) 
    cv.imwrite( "D:/binary2.png" , binary)

    #提取輪廓
    out, contours, hierarchy = cv.findContours(binary, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE) for c in range(len(contours)):         x, y, w, h = cv.boundingRect(contours[c] )         y = y - 10         h = 12         cv.rectangle(src, (x, y), (x+w, y+h), ( 0 , 0 , 255 ), 1 , 8 , 0 )     cv.imshow( " result" , src)
    

def  close_demo () :
    src = cv.imread( "D:/images/morph3.png" )
    cv.namedWindow( "input" , cv.WINDOW_AUTOSIZE)
    cv.imshow( "input" , src)

    #圖像二值化
    gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY) 
    ret, binary = cv.threshold(gray, 0 , 255 , cv.THRESH_BINARY | cv.THRESH_OTSU)

    #閉操作
     se = cv.getStructuringElement(cv.MORPH_ELLIPSE, ( 15 , 15 ), ( -1 , -1 )) 
    binary = cv.morphologyEx(binary, cv.MORPH_CLOSE, se) 
    cv.imwrite( "D:/close .png" , binary) 
    cv.imshow( "close" , binary)


close_demo() 
cv.waitKey( 0 ) 
cv.destroyAllWindows()