blockhash

Crates.ioblockhash
lib.rsblockhash
version1.0.0
sourcesrc
created_at2020-05-14 23:20:09.550572
updated_at2024-04-08 20:41:51.202621
descriptionA perceptual hashing algorithm for detecting similar images.
homepagehttps://github.com/jaehl/blockhash
repositoryhttps://github.com/jaehl/blockhash
max_upload_size
id241684
size1,429,791
J Mills (jaehl)

documentation

https://docs.rs/blockhash

README

blockhash

Crates.io CI status MIT License

This is an implementation of the Blockhash algorithm for detecting similar images, and can produce 16-, 64-, 144-, and 256-bit perceptual hashes.

Support for the image crate is provided by default, but support for any image type can be easily added.

Documentation

Usage

use blockhash::blockhash64;

let img = image::open("images/example.png").unwrap();
let hash = blockhash64(&img);

assert_eq!(hash.to_string(), "c7c48f8989c77e0c");

The Blockhash algorithm

This is a basic outline of how the algorithm works. Note that this explanation uses floating-point numbers, but the library itself only uses integer operations in order to avoid any rounding errors.

To demonstrate the algorithm, we will calculate the 64-bit hash of the following image:

First we convert it to a grayscale image by taking the average of the red, green, and blue components:

Then we divide the image into 64 (8×8) blocks and calculate the average brightness for all the pixels in each block:

Next, we divide the blocks into 4 horizontal bands and find the median value for each band:

Blocks brighter than the median represent a 1 and blocks darker than the median represent a 0. This gives us the 64 bits of the hash, read from left to right, top to bottom:

We can represent the hash as a hexadecimal string:

c7c48f8989c77e0c

License

This project is licensed under the MIT license.

Commit count: 34

cargo fmt