colorfulness v0.0.2

Colorfulness

Node.js implementation of colorfulness using node-opencv binder for OpenCV.

Related research studies

• From Rubner 2000, EMD is a good way to compare 2 images
• From Datta 2006 has used a "perfectly colored" image BGR distribution to compare image with EMD This is what they called the colorfulness measure.

Prerequisites

You will need to make node-opencv work on your local machine, so havind, opencv, node, npm.

Histograms calculation

Which image is the most colorfull ? This library will give you the answer in node.js !

Pre-requisites

• opencv

Installation

npm install colorfulness

Example

var colorfulness = require('colorfulness');

colorfulness("example/image.png", function(err, res){  
  // res is a number of colorfullness between 0 (not colorfull) and 1 (colorfull)
});

// or with open cv lib

var cv = require("opencv");
cv.readImage("example/image.png", function(err, im){
  if(err){
    //handle error
  }

  colorfulness({
    image : im
  }, function(err, res){  
    // res is a number of colorfullness between 0 (not colorfull) and 1 (colorfull)
  });
})

Test

npm test

Results

Images

Non-symetric of measure in BGR space

Remark : FFFFFF.png (white image) is more colorful than 000000.png (black image), it is because the cost function is done in the "LUV" color space.

To understand this, let's consider BGR-centers distance cost matrix in LUV_L2 distance space. To simplify my explanation i will use 2x2x2 = 8 BGR cubes (instead of 64 as used in the code);

Cubes centers are

Matrix of distance in LUV space is looks like :

So pure "cube 0"-distribution (corresponding to FFFFFF image) will not be symetric with "cube 7"-distribution (corresponding to 000000 image).

Pure "cube 4"-distribution (corresponding to 00FFFF image), is even more colorful.