img_hash Build Status

A library for getting perceptual hash values of images.

Thanks to Dr. Neal Krawetz for the outlines of the Mean (aHash), Gradient (dHash), and DCT (pHash) perceptual hash algorithms:
http://www.hackerfactor.com/blog/?/archives/432-Looks-Like-It.html (Accessed August 2014)

Thanks to Emil Mikulic for the 2D Discrete Cosine Transform implementation in C, ported to Rust in src/dct.rs:
http://unix4lyfe.org/dct/ (Implementation: http://unix4lyfe.org/dct/listing2.c) (Accessed August 2014)

With the rust-image feature, this crate can operate directly on buffers from the PistonDevelopers/image crate.

Usage

Documentation on Rust-CI

Add img_hash to your Cargo.toml:

[dependencies.img_hash]
git = "https://github.com/cybergeek94/img_hash"
# For interop with `image`:
features = ["rust-image"]

Example program:

```rust extern crate image; extern crate img_hash;

use img_hash::{ImageHash, HashType};

fn main() { let image1 = image::open(&Path::new("image1.png")).unwrap(); let image2 = image::open(&Path::new("image2.png")).unwrap();

// These two lines produce hashes with 64 bits (8 ** 2),
// using the Gradient hash, a good middle ground between 
// the performance of Mean and the accuracy of DCT.
let hash1 = ImageHash::hash(&image1, 8, HashType::Gradient);
let hash2 = ImageHash::hash(&image2, 8, HashType::Gradient);

println!("Image1 hash: {}", hash1.to_base64());
println!("Image2 hash: {}", hash2.to_base64());

println!("% Difference: {}", hash1.dist_ratio(&hash2));

} ```