使用 C++ 和 openframeworks 的 Color 图像检索系统

我正在用 C++ 和 openFrameworks 编写一个程序，希望能够通过颜色匹配来实现图像检索系统。我有一个算法可以通过 RGB 值在数据库中查找匹配项。例如，如果我的计算机上有一个包含 1000 张图片的数据库，并且我有一个查询 rgb 值 255,0,0，则程序将查找 1000 张图片并找到最接近的匹配项。然而，我的问题是我希望它也能在网络上查找匹配项。我一直在尝试寻找如何从网站获取图像，但是，如果您不知道图像的具体网址，则很难获取数据。也许有人了解如何获取网站上的图像？理想情况下，程序将在指定的网站上搜索每个网页中的图像，然后将每个图像与查询进行比较并输出最接近的匹配。

正如我在评论中提到的，这是从 RGB 颜色空间转换为 L 的问题ab* 颜色空间并使用与数据库中图像的平均颜色的欧几里德距离。

Here's a basic demo:

#include "testApp.h"

//ported from http://cookbooks.adobe.com/post_Useful_color_equations__RGB_to_LAB_converter-14227.html
struct Color{
    float R,G,B,X,Y,Z,L,a,b;
};

#define REF_X 95.047; // Observer= 2°, Illuminant= D65
#define REF_Y 100.000;
#define REF_Z 108.883;

Color rgb2xyz(int R,int G,int B){
    float r = R / 255.0;
    float g = G / 255.0;
    float b = B / 255.0;

    if (r > 0.04045){ r = pow((r + 0.055) / 1.055, 2.4); }
    else { r = r / 12.92; }
    if ( g > 0.04045){ g = pow((g + 0.055) / 1.055, 2.4); }
    else { g = g / 12.92; }
    if (b > 0.04045){ b = pow((b + 0.055) / 1.055, 2.4); }
    else {  b = b / 12.92; }

    r = r * 100;
    g = g * 100;
    b = b * 100;
    //Observer. = 2°, Illuminant = D65
    Color xyz;
    xyz.X = r * 0.4124 + g * 0.3576 + b * 0.1805;
    xyz.Y = r * 0.2126 + g * 0.7152 + b * 0.0722;
    xyz.Z = r * 0.0193 + g * 0.1192 + b * 0.9505;
    return xyz;
}
Color xyz2lab(float X,float Y, float Z){
    float x = X / REF_X;
    float y = Y / REF_X;
    float z = Z / REF_X;

    if ( x > 0.008856 ) { x = pow( x , .3333333333f ); }
    else { x = ( 7.787 * x ) + ( 16/116.0 ); }
    if ( y > 0.008856 ) { y = pow( y , .3333333333f ); }
    else { y = ( 7.787 * y ) + ( 16/116.0 ); }
    if ( z > 0.008856 ) { z = pow( z , .3333333333f ); }
    else { z = ( 7.787 * z ) + ( 16/116.0 ); }

    Color lab;
    lab.L = ( 116 * y ) - 16;
    lab.a = 500 * ( x - y );
    lab.b = 200 * ( y - z );
    return lab;
}
Color lab2xyz(float l, float a, float b){
    float y = (l + 16) / 116;
    float x = a / 500 + y;
    float z = y - b / 200;

    if ( pow( y , 3 ) > 0.008856 ) { y = pow( y , 3 ); }
    else { y = ( y - 16 / 116 ) / 7.787; }
    if ( pow( x , 3 ) > 0.008856 ) { x = pow( x , 3 ); }
    else { x = ( x - 16 / 116 ) / 7.787; }
    if ( pow( z , 3 ) > 0.008856 ) { z = pow( z , 3 ); }
    else { z = ( z - 16 / 116 ) / 7.787; }

    Color xyz;
    xyz.X = x * REF_X;
    xyz.Y = y * REF_Y;
    xyz.Z = z * REF_Z;
    return xyz;
}
Color xyz2rgb(float X,float Y,float Z){
    //X from 0 to  95.047      (Observer = 2°, Illuminant = D65)
    //Y from 0 to 100.000
    //Z from 0 to 108.883
    X = ofClamp(X, 0, 95.047);

    float x = X * .01;
    float y = Y * .01;
    float z = Z * .01;

    float r = x * 3.2406 + y * -1.5372 + z * -0.4986;
    float g = x * -0.9689 + y * 1.8758 + z * 0.0415;
    float b = x * 0.0557 + y * -0.2040 + z * 1.0570;

    if ( r > 0.0031308 ) { r = 1.055 * pow( r , ( 1 / 2.4f ) ) - 0.055; }
    else { r = 12.92 * r; }
    if ( g > 0.0031308 ) { g = 1.055 * pow( g , ( 1 / 2.4f ) ) - 0.055; }
    else { g = 12.92 * g; }
    if ( b > 0.0031308 ) { b = 1.055 * pow( b , ( 1 / 2.4f ) ) - 0.055; }
    else { b = 12.92 * b; }

    Color rgb;
    rgb.R = round( r * 255 );
    rgb.G = round( g * 255 );
    rgb.B = round( b * 255 );
    return rgb;
}
Color rgb2lab(int R,int G,int B){
    Color xyz = rgb2xyz(R, G, B);
    return xyz2lab(xyz.X, xyz.Y, xyz.Z);
}
Color lab2rgb(int L,int a,int b){
    Color xyz = lab2xyz(L, a, b);
    return xyz2rgb(xyz.X, xyz.Y, xyz.Z);
}

Color getAverage(ofImage img){
    Color avg;
    avg.L = avg.a = avg.b = 0;

    int total = img.width * img.height;
    for(int y = 0 ; y < img.height; y++){
        for(int x = 0 ; x < img.width; x++){
            ofColor c = img.getColor(x, y);
            Color lab = rgb2lab(c.r,c.g,c.b);
            avg.L += lab.L;
            avg.a += lab.a;
            avg.b += lab.b;
        }
    }

    avg.L /= total;
    avg.a /= total;
    avg.b /= total;
    return avg;
}
ofImage images[6];
Color   averages[6];
ofColor averagesRGB[6];

ofImage colorPicker;
ofColor searchClr;

int closestId = -1;

//--------------------------------------------------------------
void testApp::setup(){
    colorPicker.loadImage("colormap.gif");

    images[0].loadImage("red.jpg");
    images[1].loadImage("green.jpg");
    images[2].loadImage("blue.jpg");
    images[3].loadImage("cyan.jpg");
    images[4].loadImage("magenta.jpg");
    images[5].loadImage("yellow.jpg");

    for(int i = 0 ;  i < 6; i++){
        averages[i] = getAverage(images[i]);
        Color avgRGB = lab2rgb(averages[i].L, averages[i].a, averages[i].b);
        averagesRGB[i] = ofColor(avgRGB.R,avgRGB.G,avgRGB.B);
    }

}

//--------------------------------------------------------------
void testApp::update(){
    //pick a colour
    searchClr = colorPicker.getColor(mouseX,mouseY-500);
    //find closest - might want to that on an event
    Color searchLab = rgb2lab(searchClr.r, searchClr.g, searchClr.b);
    float minDist = 10000000;
    for(int i = 0 ; i < 6; i++){
        Color Lab = averages[i];
        float dL = Lab.L - searchLab.L;
        float da = Lab.a - searchLab.a;
        float db = Lab.b - searchLab.b;
        float dist = sqrt(dL*dL + da*da + db*db);
        if(dist < minDist){
            minDist = dist;
            closestId = i;
        }
    }
}

//--------------------------------------------------------------
void testApp::draw(){
    for(int i = 0 ;  i < 6; i++){
        //indexed image
        images[i].draw(images[i].width * i, 0);
        //average colour
        ofPushStyle();
        ofSetColor(averagesRGB[i]);
        ofRect(images[i].width * i, images[i].height, images[i].width, images[i].width);
        ofPopStyle();
    }
    ofPushStyle();
    ofSetColor(searchClr);
    ofRect(200,500,200,200);
    ofPopStyle();
    colorPicker.draw(0,500);
    if(closestId >= 0){
        images[closestId].draw(400, 500);
    }
}

//--------------------------------------------------------------
void testApp::keyPressed(int key){

}

//--------------------------------------------------------------
void testApp::keyReleased(int key){

}

//--------------------------------------------------------------
void testApp::mouseMoved(int x, int y){

}

//--------------------------------------------------------------
void testApp::mouseDragged(int x, int y, int button){

}

//--------------------------------------------------------------
void testApp::mousePressed(int x, int y, int button){

}

//--------------------------------------------------------------
void testApp::mouseReleased(int x, int y, int button){

}

//--------------------------------------------------------------
void testApp::windowResized(int w, int h){

}

//--------------------------------------------------------------
void testApp::gotMessage(ofMessage msg){

}

//--------------------------------------------------------------
void testApp::dragEvent(ofDragInfo dragInfo){ 

}

编码风格并不出色，但它只是为了说明这个想法。当然，您需要首先从 url 加载图像并在 L 中索引平均颜色ab* 代表数据库中的每个（运行时或其他情况下的向量）。 上面的代码也可以作为Xcode项目 http://lifesine.eu/so/LABTest.zip