Block Hash

Block hashing is based on five steps:

(1) Resize an image to be a squared image of height and width equal to a user defined input hash_size.
(2) Construct a matrix img_resized_gray with the gray values of the resized image.
(3) Split the image into 4 quadrants and determine which quadrant has the highest total brightness.
(4) Flip the image horizontally and/or vertically so that the brightest quadrant ends up in the top-left.
(5) Compute the median intensity of the flipped image and build a matrix that contains a 1 in position k if flipped[k] > median, and a 0 otherwise.

The block hash vector for an image would be the flattened matrix of step (5).

Example

Let us visualize the original image and hash and mathash of an image.

using TestImages
img = testimage("fabio_color_256.png");
img

A block mat hash (matrix hash) can be created using block_mathash(image, hash_size), as follows:

using TestImages, Images, ImageHashes
img = testimage("fabio_color_256.png");
mat_hash = block_mathash(img, hash_size=8)
mat_hash

8×8 BitMatrix:
 1  1  1  1  0  0  0  1
 0  1  1  1  0  0  1  1
 0  0  1  1  1  0  1  1
 0  0  1  1  1  0  1  1
 0  0  1  1  1  0  1  0
 0  0  1  1  1  0  0  0
 0  0  0  1  1  1  0  0
 0  0  0  1  1  0  0  0

We can visualize the hash using Gray..

using TestImages, Images, ImageHashes
img = testimage("fabio_color_256.png");
mat_hash = block_mathash(img, hash_size=8)
Gray.(mat_hash)

The bigger the mat hash is, the higher quality it can achieve.

using TestImages, Images, ImageHashes
img = testimage("fabio_color_256.png");
mat_hash = block_mathash(img, hash_size=28)
Gray.(mat_hash)

A hash (vector hash) for an image can be created with the block_hash function.

using TestImages, ImageHashes
img = testimage("fabio_color_256.png");
img_hash = block_hash(img, hash_size=8)
img_hash

0x80c0fcff3f0278f0

Execution time and allocations

using TestImages, ImageHashes, BenchmarkTools
img = testimage("fabio_color_256.png");
benchmark = @benchmark block_hash($img, hash_size=8)
benchmark

BenchmarkTools.Trial: 10000 samples with 1 evaluation per sample.
 Range (min … max):  116.075 μs …  1.988 ms  ┊ GC (min … max): 0.00% … 92.59%
 Time  (median):     116.867 μs              ┊ GC (median):    0.00%
 Time  (mean ± σ):   123.714 μs ± 50.000 μs  ┊ GC (mean ± σ):  1.01% ±  2.44%

  ██▃▁ ▁        ▄▄▂▁                  ▁▂▂▂▂▂▂▂▁▁▁              ▂
  ████▇██▆▆▅▃▃▄▇█████▇▇▆▅▅▅▃▄▃▄▁▃▄▄▇█████████████▇▇▆▆▅▇▆▇▇▇▇█▇ █
  116 μs        Histogram: log(frequency) by time       158 μs <

 Memory estimate: 64.81 KiB, allocs estimate: 9.