图像检索系统的颜色从web使用C ++与openframeworks [英] Image retrieval system by Colour from the web using C++ with openframeworks
问题描述
我在C ++和openFrameworks编写一个应该希望通过颜色匹配实现图像检索系统的程序。我有一个算法，通过rgb值在数据库中找到匹配。例如，如果我有一个1000个图片在我的计算机上的数据库，我有一个查询rgb值255,0,0的程序将查看1000张图片，找到最接近的匹配。但是，我的问题是，我希望它也在网上寻找匹配。我一直在试图找到如何从网站获取图像，但是，如果你不知道图像的具体网址，很难得到的数据。也许有人知道如何抓住网站上的图像？理想情况下，程序将进入指定的网站并搜索图像的每个网页，然后将每个图像与查询进行比较并输出最接近的匹配。
I am writing a program in C++ and openFrameworks that should hopefully implement an image retrieval system by colour matching. I have got an algorithm to find the match in a database by an rgb value. For example, if I have a database of 1000 pictures on my computer and I have a query rgb value 255,0,0 the program would look through 1000 pictures and find the closest match. However, my problem is that I want it to also look for the match on the web. I have been trying to find how to get images from websites, however, if you don't know the specific url of the image it's hard to get hold of the data. Maybe somebody has got some knowledge of how to get hold of images on websites? Ideally, the program would go on specified website and search through every webpage for the images, it would then compare each image to the query and output the closest match.
推荐答案
正如我在评论中提到的，它是从RGB颜色空间转换为L b * colourspace和使用欧氏距离到图像的平均颜色从数据库。
As I mentioned in my comment, it's a matter of converting from RGB colourspace to Lab* colourspace and using the euclidean distance to the average colour of the image from the database.
这是一个基本的演示：
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){
}
编码风格不是很好，但它只是为了说明这个想法。当然，您需要先从网址中加载图片，然后在数据库（运行时的向量或其他方式）中为每个元素在L a b *中索引平均颜色。
上述代码也可作为 Xcode项目使用
The coding style isn't brilliant but it's just to illustrate the idea. Of course you would need to load the images from the url first and index the average colour in Lab* for each in a database (vector at runtime or otherwise). The above code is also available as an Xcode project
这篇关于图像检索系统的颜色从web使用C ++与openframeworks的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
