Opencv+Qt 颜色识别简单例子

在这个例子中，我们开始选定一种颜色，并设置一个阈值

然后把图片中和所选颜色的差别在阈值中的点标定出来

在这个例子中，主要要注意这两点：

1. OpenCV与QT的结合，包括Mat 与 QImage 的转换

2. 我们使用了类来实现此功能，创建了一个单例模式的类

首先我们创建一个简单的图形界面，使用的是QT

创建处理图像用的类

#ifndef COLORDETECTOR_H_#define COLORDETECTOR_H_#include <opencv2/core/core.hpp>#include <opencv2/highgui/highgui.hpp>#include <string>class ColorDetector{private:        int minDist;        cv::Vec3b target;        cv::Mat result;        cv::Mat image;        ColorDetector();        static ColorDetector *singleton;public:        static ColorDetector * getInstance();        static void destory();        void setColorDistanceThreshold(int);        int getColorDistanceThreshold() const;        void setTargetColor(unsigned char, unsigned char, unsigned char);        void setTargetColor(cv::Vec3b);        cv::Vec3b getTargetColor() const;        void process();        int getDistance(const cv::Vec3b&) const;        cv::Mat getResult() const;        bool setInputImage(std::string);        cv::Mat getInputImage() const;};#endif /* COLORDETECTOR_H_ */

将其构造函数声明为private，提供静态的接口来获得ColorDetector对象

void setColorDistanceThreshold(int) 用于设置阈值
void setTargetColor(unsigned char, unsigned char, unsigned char)
void setTargetColor(cv::Vec3b) 用于设置颜色
bool setInputImage(std::string) 用于载入待处理图像
cv::Mat getResult() const 用于返回处理结果，结果用一副图像表示

其具体实现如下

#include "ColorDetector.h"ColorDetector* ColorDetector::singleton = 0;ColorDetector::ColorDetector():minDist(100){        target[0] = target[1] = target[2] = 0;}ColorDetector* ColorDetector::getInstance(){        if(singleton == 0){                singleton = new ColorDetector;        }        return singleton;}void ColorDetector::destory(){        if(singleton!=0){                delete singleton;        }        singleton = 0;}void ColorDetector::setColorDistanceThreshold(int distance){        if(distance < 0){                distance = 0;        }        minDist = distance;}int ColorDetector::getColorDistanceThreshold() const{        return minDist;}void ColorDetector::setTargetColor(unsigned char red,                unsigned char green, unsigned char blue){        target[2] = red;        target[1] = green;        target[0] = blue;}void ColorDetector::setTargetColor(cv::Vec3b color){        target = color;}cv::Vec3b ColorDetector::getTargetColor() const{        return target;}int ColorDetector::getDistance(const cv::Vec3b& color) const{        return abs(color[0]-target[0])+abs(color[1]-target[1])+abs(color[2]-target[2]);}void ColorDetector::process(){        result.create(image.rows, image.cols, CV_8U);        cv::Mat_<cv::Vec3b>::const_iterator it = image.begin<cv::Vec3b>();        cv::Mat_<cv::Vec3b>::const_iterator itend = image.end<cv::Vec3b>();        cv::Mat_<uchar>::iterator itout = result.begin<uchar>();        for(; it!=itend; ++it, ++itout){                if(getDistance(*it) < minDist){                        *itout = 255;                }else{                        *itout = 0;                }        }}cv::Mat ColorDetector::getResult() const{        return result;}bool ColorDetector::setInputImage(std::string filename){        image = cv::imread(filename);        if(!image.data){                return false;        }        return true;}cv::Mat ColorDetector::getInputImage() const{        return image;}

在前面文章中，讲了遍历像素点的方法，这里用迭代器实现

然后是图像界面中的处理函数

#ifndef WIDGET_H#define WIDGET_H#include <QWidget>#include <QFileDialog>#include <QImage>#include <opencv2/core/core.hpp>#include <opencv2/highgui/highgui.hpp>#include <opencv2/imgproc/imgproc.hpp>#include "colordetector.h"namespace Ui {    class Widget;}class Widget : public QWidget{    Q_OBJECTpublic:    explicit Widget(QWidget *parent = 0);    ~Widget();private:    Ui::Widget *ui;    QImage qimage;    cv::Mat image;private slots:    void openImage();    void dealImage();    void colorSelect();    void changeDis(int);};#endif // WIDGET_H

其实现

#include "widget.h"#include "ui_widget.h"#include <QColorDialog>Widget::Widget(QWidget *parent) :    QWidget(parent),    ui(new Ui::Widget){    ui->setupUi(this);    connect(ui->openImage,SIGNAL(clicked()),this,SLOT(openImage()));    connect(ui->dealImage,SIGNAL(clicked()),this,SLOT(dealImage()));    connect(ui->colorButton,SIGNAL(clicked()),this,SLOT(colorSelect()));    connect(ui->verticalSlider,SIGNAL(valueChanged(int)),this,SLOT(changeDis(int)));}Widget::~Widget(){    delete ui;}void Widget::openImage(){    QString fileName = QFileDialog::getOpenFileName(this,                  tr("Open Image"), ".",                tr("Image Files (*.png *.jpg *.jpeg *.bmp)"));    ColorDetector::getInstance()->setInputImage(fileName.toAscii().data());    cv::namedWindow("image");    cv::imshow("image",ColorDetector::getInstance()->getInputImage());    dealImage();}void Widget::dealImage(){    ColorDetector::getInstance()->process();    cv::cvtColor(ColorDetector::getInstance()->getResult(),image,CV_GRAY2RGB);    qimage = QImage((const unsigned char*)(image.data),image.cols,image.rows,QImage::Format_RGB888);    ui->label->setPixmap(QPixmap::fromImage(qimage).scaledToHeight(300));    //ui->label->resize(ui->label->pixmap()->size());}void Widget::colorSelect(){    QColor color = QColorDialog::getColor(Qt::green,this);    if(color.isValid()){        ColorDetector::getInstance()->setTargetColor(                    color.red(),color.green(),color.blue());    }    dealImage();}void Widget::changeDis(int value){    ColorDetector::getInstance()->setColorDistanceThreshold(value);    dealImage();}

在QT项目的pro文件中要加入如下几句

INCLUDEPATH += D:\OpenCV\include
LIBS += -LD:\OpenCV\lib \
-lopencv_core230 \
-lopencv_highgui230 \
-lopencv_imgproc230

看看最后效果

不同颜色，不同阈值的比较效果

转载自:http://www.cnblogs.com/xianglan/archive/2011/07/31/2122719.html