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average_hash

calculation of the 'average hash' of an image


Description

This function calculates the average hash of an image

Usage

average_hash(gray_image, hash_size = 8, MODE = "hash", resize = "nearest")

Arguments

gray_image

a (2-dimensional) matrix or data frame

hash_size

an integer specifying the hash size (should be less than number of rows or columns of the gray_image)

MODE

one of 'hash' (returns the hash of the image), 'binary' (returns binary identifier of the image)

resize

corresponds to one of 'nearest', 'bilinear' (resizing method)

Details

The function is a modification of the 'average_hash' function of the imagehash package [ please consult the COPYRIGHT file ]. The average hash works in the following way : 1st convert to grayscale, 2nd, reduce the size of an image (for instance to an 8x8 image, to further simplify the number of computations), 3rd average the resulting colors (for an 8x8 image we average 64 colors), 4th compute the bits by comparing if each color value is above or below the mean, 5th construct the hash.

Value

either a hash-string or a binary vector

Examples

image = readImage(system.file("tmp_images", "1.png", package = "OpenImageR"))

image = rgb_2gray(image)

res_hash = average_hash(image, hash_size = 8, MODE = 'hash')

res_binary = average_hash(image, hash_size = 8, MODE = 'binary')

OpenImageR

An Image Processing Toolkit

v1.1.8
GPL-3
Authors
Lampros Mouselimis [aut, cre] (<https://orcid.org/0000-0002-8024-1546>), Sight Machine [cph] (findHOGFeatures function of the SimpleCV computer vision platform), Johannes Buchner [cph] (average_hash, dhash and phash functions of the ImageHash python library), Mohammad Haghighat [cph] (Gabor Feature Extraction), Radhakrishna Achanta [cph] (Author of the C++ code of the SLIC and SLICO algorithms (for commercial use please contact the author))
Initial release
2021-05-04

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