The best colour extractor tool helps you find CMYK and Pantone colour codes for your labelling and packaging artwork

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Colour extraction is a process where a computer looks at an image and makes a reasonable guess at which colours are being used in that image. This can be useful when you need to get the exact colour used on a website or piece of branding artwork, but don’t have access to the source files for that artwork.

Paste the URL of an online image:

Press the “Paste Image URL” button.

The colour extractor will automatically find the colours and generate a palette for you. You can also select a specific colour from your image to create the swatch file that you can use in your design tool.

1. What is colour extraction? 

The Colour Extractor Service, given an image, can calculate a histogram of the colours of pixels, and order them into buckets based on their dominant colours. Color-Extraction is an open-source Python module that assigns the most similar colours to each item in an NDARray (RGB image) from a preset palette of colours. The colour palette generator in Workbench extracts a set of HEX colours from the image when it is uploaded. The colours within the pixels of an image are bucketed in 40 dominant colours that are representative of the colour spectrum. 

Using our online tools, you can extract dominant colours from the image and create a colour palette that matches the image subject. If you would like to extract colours from an image online, you first need to download it on your device, and then drop the downloaded file into the tool above. The following example requests extracting colours from the image according to the input parameters provided in the payload. The following example request uses this method to extract colours. 

The text colour library returns an RGB value, which will be converted into a HEX colour code using the rgb2hex library. Clicking the tint will copy the HEX values to the clipboard. 

If limit=12) is set to have more than 12 colours, you may want to adjust your X-axis and Y-axis values to fit your results. We can take this one step further, increasing the tolerance to 36 to obtain a larger code for pink colours. We are going to raise the number of tolerances to 24. Exact_Color(example.jpg, 900, 24, 2.5) The result after setting the tolerance values equal to 24. 

It is also possible to use custom colour definitions saved to the JSON file. The extraction methods may also differ depending on how colour is contained in a natural source: if colour is in the outside parts of a harvest, the meat, or parts of a seed. When colour is located on the outside part of the source, such as with purple corn, carmine, and spirulina, water extraction is an excellent option. 

Each of these arrays has the same horizontal and vertical dimensions as the original image and can be thought of as masking for the colour in question. These keys hold a string representing the name of the colour, a percentage of how much that colour appears about the image sent to the content_id, and the RGB values for that colour. For example, the image might include metadata describing the size of the picture, colour depth, image resolution, creation date, and other data. 

This is a tough question to answer, but Russell Dinnage uses the clustering capabilities of the Rs k-means function to extract the 3 (or 4 or 6 – take your pick) most dominant colours from the image, while not including near-identical shades of the same colour, and removing lower-saturation background colours (such as grey shadows). 


Colour extraction, also known as colour profile extraction, is a process where a computer looks at an image and makes a reasonable guess at which colours are being used in that image. For example, if you have an image with yellow and blue popsicles on one side of the page and red cupcakes on another side of the same page, then it should be possible for the software to determine which colours are contained within each popsicle/cupcake pair.

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