https://github.com/cawfree/otsu

✂️ Otsu's Method for automated thresholding in JavaScript.
https://github.com/cawfree/otsu

image processing segmentation threshold

Last synced: 3 months ago
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✂️ Otsu's Method for automated thresholding in JavaScript.

• Host: GitHub
• URL: https://github.com/cawfree/otsu
• Owner: cawfree
• License: mit
• Created: 2020-02-05T09:34:47.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2023-12-02T17:35:22.000Z (about 1 year ago)
• Last Synced: 2024-09-17T15:28:53.962Z (5 months ago)
• Topics: image, processing, segmentation, threshold
• Language: JavaScript
• Homepage:
• Size: 1.07 MB
• Stars: 14
• Watchers: 3
• Forks: 1
• Open Issues: 12
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# otsu

[Otsu's Method](https://en.wikipedia.org/wiki/Otsu%27s_method) is way of implementing automatic thresholding. It is a binarization algorithm which can be used to select the optimal threshold between foreground and background quantities based on finding the minimum point of cross variance. This is particularly useful when performing segmentation in [image processing](https://en.wikipedia.org/wiki/Digital_image_processing).



    











  



You can find an awesome description of the algorithm, which inspired this repository, [here](http://www.labbookpages.co.uk/software/imgProc/otsuThreshold.html).

## 🚀 Getting Started

Using [`npm`](https://www.npmjs.com/):

```bash

npm install --save otsu

```

Using [`yarn`](https://yarnpkg.com/):

```bash

yarn add otsu

```

## ✍️ Usage

It's really simple to find the threshold of your image. All you have to do is supply the data!

In the example below, we have a one-dimensional array of intensity data. Most greyscale image formats, such as [MNIST](http://yann.lecun.com/exdb/mnist/), can be fed directly into otsu this way. However, images that consist of multiple attributes per pixel (such as `(r,g,b)`) will first require pre-processing.

```javascript

import otsu from 'otsu';

const intensity = [255, 0, 128, 4, 95 ...];

const t = otsu(intensity);

console.log(t); // i.e. 128

const thresholded = intensity.map(e => (e > t ? 1 : 0));

```

## ✌️ License

[MIT](https://opensource.org/licenses/MIT)