Opencv通过颜色区分电线

Opencv检测不同颜色的电线是否接好

机器视觉检测物体要根据检测对象的特征找到最方便快捷的方法，最近做了一个靠颜色像素来区分电线的小项目，颜色区分是inRange方法，这个方法检测的是HSV彩色图像的范围，需要将图像转换为HSV图像。

如图，要检测图中六条线是否都接好并且位置没有错误，观察背景，大多都是灰黑色的物体，只有这些电线颜色比较鲜明，因此选择用颜色像素来区分。
设计算法：其实也没有什么算法，每个线的颜色范围，就是用制图工具来采集一下各个颜色的BGR像素范围，因为每条线的亮度并不完全一样，只要获取看起来最亮的一点和看起来最暗的一点，就能获取到每天直线的颜色像素范围，但是要检测的不仅仅是存不存在，还要检测各个线的位置是否正确，由于这张图较大，所以应该先获取到电线的大概位置，那么就要利用图中其他明显的特征，如图，下面的接头是红色的，这片红色在图中占的比例较大，而且比较方面寻找，所以可以先找一下这个红色的接头

找到之后，就能获取红色接头的位置，因为相机与接线的位置都是固定的，所以每次拍的照片都不会差太多，那么只要能找到这个红色接头，为它做一个外包矩形，根据矩形的中点，向右移动部分像素，这个要根据实际情况决定，然后大概得到一个范围，把六条线的位置可以剪切出来。

如图，切出这样一张图之后，就可以根据颜色来区分每条线是否接好以及位置是否正确。因为我们获取的像素范围是BGR的，所以需要自己计算成HSV的。

代码如下：

def rgb2hsv(r, g, b):
    r, g, b = r/255.0, g/255.0, b/255.0
    mx = max(r, g, b)
    mn = min(r, g, b)
    m = mx-mn
    if mx == mn:
        h = 0
    elif mx == r:
        if g >= b:
            h = ((g-b)/m)*60
        else:
            h = ((g-b)/m)*60 + 360
    elif mx == g:
        h = ((b-r)/m)*60 + 120
    elif mx == b:
        h = ((r-g)/m)*60 + 240
    if mx == 0:
        s = 0
    else:
        s = m/mx
    v = mx
    H = h / 2
    S = s * 255.0
    V = v * 255.0
    return H, S, V

得到了像素范围之后，就要去检测各个线的位置，以红色为例：

def redFind(image):
    lower = np.array([168, 43, 46])
    upper = np.array([180, 255, 255])
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsv, lower, upper)
    s = cv2.getStructuringElement(cv2.MORPH_RECT,(5,5))
    openI = cv2.morphologyEx(mask,cv2.MORPH_OPEN,s,iterations=1)
    closeI = cv2.morphologyEx(openI,cv2.MORPH_CLOSE,s,iterations=1)
    contours, hierarchy = cv2.findContours(closeI, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for c in contours:
        rect = cv2.minAreaRect(c)
        print("红色:", int((rect[0][1] + rect[1][1]/2)))

    cv2.imshow("aaa", closeI)
    cv2.waitKey(1000)

如图得到了红色电线的二值图像，通过最小外接矩形可以得到它的大概位置，如下图这是各个直线中点的纵向坐标。

附上代码：
Python代码：

import cv2 
import numpy as np 

def redFind(image):
    lower = np.array([168, 43, 46])
    upper = np.array([180, 255, 255])
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsv, lower, upper)
    s = cv2.getStructuringElement(cv2.MORPH_RECT,(5,5))
    openI = cv2.morphologyEx(mask,cv2.MORPH_OPEN,s,iterations=1)
    closeI = cv2.morphologyEx(openI,cv2.MORPH_CLOSE,s,iterations=1)
    contours, hierarchy = cv2.findContours(closeI, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for c in contours:
        rect = cv2.minAreaRect(c)
        print("红色:", int((rect[0][1] + rect[1][1]/2)))

    cv2.imshow("aaa", closeI)
    cv2.waitKey(1000)

def purpleFind(image):
    lower = np.array([142, 43, 46])
    upper = np.array([147, 255, 255])
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsv, lower, upper)
    s = cv2.getStructuringElement(cv2.MORPH_RECT,(5,5))
    openI = cv2.morphologyEx(mask,cv2.MORPH_OPEN,s,iterations=1)
    closeI = cv2.morphologyEx(openI,cv2.MORPH_CLOSE,s,iterations=1)
    contours, hierarchy = cv2.findContours(closeI, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for c in contours:
        rect = cv2.minAreaRect(c)
        print("紫色:", int((rect[0][1] + rect[1][1]/2)))

    cv2.imshow("aaa", closeI)
    cv2.waitKey(1000)

def blueFind(image):
    lower = np.array([102, 43, 46])
    upper = np.array([112, 255, 255])
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsv, lower, upper)
    s = cv2.getStructuringElement(cv2.MORPH_RECT,(5,5))
    openI = cv2.morphologyEx(mask,cv2.MORPH_OPEN,s,iterations=1)
    closeI = cv2.morphologyEx(openI,cv2.MORPH_CLOSE,s,iterations=1)
    contours, hierarchy = cv2.findContours(closeI, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for c in contours:
        rect = cv2.minAreaRect(c)
        print("蓝色:", int((rect[0][1] + rect[1][1]/2)))

    cv2.imshow("aaa", closeI)
    cv2.waitKey(1000)

def yellowFind(image):
    lower = np.array([20, 43, 46])
    upper = np.array([25, 255, 255])
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsv, lower, upper)
    s = cv2.getStructuringElement(cv2.MORPH_RECT,(5,5))
    openI = cv2.morphologyEx(mask,cv2.MORPH_OPEN,s,iterations=1)
    closeI = cv2.morphologyEx(openI,cv2.MORPH_CLOSE,s,iterations=1)
    contours, hierarchy = cv2.findContours(closeI, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for c in contours:
        rect = cv2.minAreaRect(c)
        print("黄色:", int((rect[0][1] + rect[1][1]/2)))

    cv2.imshow("aaa", closeI)
    cv2.waitKey(1000)

def orangeFind(image):
    lower = np.array([11, 43, 46])
    upper = np.array([15, 255, 255])
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsv, lower, upper)
    s = cv2.getStructuringElement(cv2.MORPH_RECT,(7,7))
    openI = cv2.morphologyEx(mask,cv2.MORPH_OPEN,s,iterations=1)
    closeI = cv2.morphologyEx(openI,cv2.MORPH_CLOSE,s,iterations=1)
    contours, hierarchy = cv2.findContours(closeI, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for c in contours:
        rect = cv2.minAreaRect(c)
        print("橙色:", int((rect[0][1] + rect[1][1]/2)))

    cv2.imshow("aaa", closeI)
    cv2.waitKey(1000)

def brownFind(image):
    lower = np.array([3, 43, 46])
    upper = np.array([8, 255, 255])
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsv, lower, upper)
    s = cv2.getStructuringElement(cv2.MORPH_RECT,(5,5))
    openI = cv2.morphologyEx(mask,cv2.MORPH_OPEN,s,iterations=1)
    closeI = cv2.morphologyEx(openI,cv2.MORPH_CLOSE,s,iterations=1)
    contours, hierarchy = cv2.findContours(closeI, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    for c in contours:
        rect = cv2.minAreaRect(c)
        print("棕色:", int((rect[0][1] + rect[1][1]/2)))

    cv2.imshow("aaa", closeI)
    cv2.waitKey(1000)

if __name__ == "__main__":
    image = cv2.imread("ceshi.png")
    purpleFind(image)
    orangeFind(image)
    yellowFind(image)
    brownFind(image)
    blueFind(image)
    redFind(image)

C++代码：
// coloranalyze.cpp : 此文件包含 “main” 函数。程序执行将在此处开始并结束。
//

#include "pch.h"
#include <iostream>
#include <opencv2/core/core.hpp>              
#include <opencv2/highgui/highgui.hpp>              
#include <opencv2/imgproc/imgproc.hpp>  

using namespace std;
using namespace cv;

double purpleFind(Mat image);
double orangeFind(Mat image);
double yellowFind(Mat image);
double brownFind(Mat image);
double blueFind(Mat image);
double redFind(Mat image);

struct returnData
{
	double colorNumber[10];
	double line_y[10];
};

int main()
{
	Mat srcImage = imread("D:\\code\\code\\ceshi.png");
	Mat srcImage1;
	cvtColor(srcImage, srcImage1, COLOR_BGR2HSV);
	double y0, y1, y2, y3, y4, y5;
	returnData colorline;
	y0 = purpleFind(srcImage1);
	colorline.colorNumber[0] = 0;
	colorline.line_y[0] = y0;
	y1 = orangeFind(srcImage1);
	colorline.colorNumber[1] = 1;
	colorline.line_y[1] = y1;
	y2 = yellowFind(srcImage1);
	colorline.colorNumber[2] = 2;
	colorline.line_y[2] = y2;
	y3 = brownFind(srcImage1);
	colorline.colorNumber[3] = 3;
	colorline.line_y[3] = y3;
	y4 = blueFind(srcImage1);
	colorline.colorNumber[4] = 4;
	colorline.line_y[4] = y4;
	y5 = redFind(srcImage1);
	colorline.colorNumber[5] = 5;
	colorline.line_y[5] = y5;

	for (int i = 0; i < 6; i++) {
		cout << colorline.colorNumber[i] << endl;
		cout << colorline.line_y[i] << endl;

	}
	
	return 1;
	
}



double purpleFind(Mat image)
{
	Mat dstImage;
	inRange(image, Scalar(142, 43, 46), Scalar(147, 255, 255), dstImage);
	Mat s, openImage, closeImage;
	s = getStructuringElement(MORPH_RECT, Size(5, 5));
	morphologyEx(dstImage, openImage, MORPH_OPEN, s, Point(-1, -1), 1);
	morphologyEx(openImage, closeImage, MORPH_CLOSE, s, Point(-1, -1), 1);
	vector<vector<Point>> contours;
	findContours(closeImage, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
	Rect rect;
	rect = boundingRect(contours[0]);
	int line_y;
	line_y = rect.y + rect.height / 2;
	cout << line_y << endl;
	
	return line_y;
}

double orangeFind(Mat image)
{
	Mat dstImage;
	inRange(image, Scalar(11, 43, 46), Scalar(15, 255, 255), dstImage);
	Mat s, openImage, closeImage;
	s = getStructuringElement(MORPH_RECT, Size(7, 7));
	morphologyEx(dstImage, openImage, MORPH_OPEN, s, Point(-1, -1), 1);
	morphologyEx(openImage, closeImage, MORPH_CLOSE, s, Point(-1, -1), 1);
	vector<vector<Point>> contours;
	findContours(closeImage, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
	Rect rect;
	rect = boundingRect(contours[0]);
	int line_y;
	line_y = rect.y + rect.height / 2;
	cout << line_y << endl;
	return line_y;
}

double yellowFind(Mat image)
{
	Mat dstImage;
	inRange(image, Scalar(20, 43, 46), Scalar(25, 255, 255), dstImage);
	Mat s, openImage, closeImage;
	s = getStructuringElement(MORPH_RECT, Size(5, 5));
	morphologyEx(dstImage, openImage, MORPH_OPEN, s, Point(-1, -1), 1);
	morphologyEx(openImage, closeImage, MORPH_CLOSE, s, Point(-1, -1), 1);
	vector<vector<Point>> contours;
	findContours(closeImage, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
	Rect rect;
	rect = boundingRect(contours[0]);
	int line_y;
	line_y = rect.y + rect.height / 2;
	cout << line_y << endl;
	return line_y;
}

double brownFind(Mat image)
{
	Mat dstImage;
	inRange(image, Scalar(3, 43, 46), Scalar(8, 255, 255), dstImage);
	Mat s, openImage, closeImage;
	s = getStructuringElement(MORPH_RECT, Size(5, 5));
	morphologyEx(dstImage, openImage, MORPH_OPEN, s, Point(-1, -1), 1);
	morphologyEx(openImage, closeImage, MORPH_CLOSE, s, Point(-1, -1), 1);
	vector<vector<Point>> contours;
	findContours(closeImage, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
	Rect rect;
	rect = boundingRect(contours[0]);
	int line_y;
	line_y = rect.y + rect.height / 2;
	cout << line_y << endl;
	return line_y;
}

double blueFind(Mat image)
{
	Mat dstImage;
	inRange(image, Scalar(102, 43, 46), Scalar(112, 255, 255), dstImage);
	Mat s, openImage, closeImage;
	s = getStructuringElement(MORPH_RECT, Size(5, 5));
	morphologyEx(dstImage, openImage, MORPH_OPEN, s, Point(-1, -1), 1);
	morphologyEx(openImage, closeImage, MORPH_CLOSE, s, Point(-1, -1), 1);
	vector<vector<Point>> contours;
	findContours(closeImage, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
	Rect rect;
	rect = boundingRect(contours[0]);
	int line_y;
	line_y = rect.y + rect.height / 2;
	cout << line_y << endl;
	return line_y;
}

double redFind(Mat image)
{
	Mat dstImage;
	inRange(image, Scalar(168, 43, 46), Scalar(180, 255, 255), dstImage);
	Mat s, openImage, closeImage;
	s = getStructuringElement(MORPH_RECT, Size(5, 5));
	morphologyEx(dstImage, openImage, MORPH_OPEN, s, Point(-1, -1), 1);
	morphologyEx(openImage, closeImage, MORPH_CLOSE, s, Point(-1, -1), 1);
	vector<vector<Point>> contours;
	findContours(closeImage, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
	Rect rect;
	rect = boundingRect(contours[0]);
	int line_y;
	line_y = rect.y + rect.height / 2;
	cout << line_y << endl;

	return line_y;
}