Similar picture identification method, device, and storage medium

A computer device, comprising:

• processing circuitry configured to:
• identify n first local regions of a first picture, the n first local regions being a first set of regions that is affine invariant;
• identify m second local regions of a second picture, the m second local regions being a second set of regions that is affine invariant;
• obtain n first characteristic values respectively corresponding to the n first local regions, and obtaining m second characteristic values respectively corresponding to the m second local regions, the first characteristic values representing feature information of the first local regions, and the second characteristic values representing feature information of the second local regions;
• and
• determine, according to a comparison result of the n first characteristic values and the m second characteristic values, whether the first picture is similar to the second picture, wherein
• n and m are positive integers.

A method of determining picture key characteristics, comprising:

• identifying, by processing circuitry of a device, key regions in one or more pictures;
• calculating, by the processing circuitry, fingerprints respectively corresponding to the picture key characteristics in the key regions;
• grouping the fingerprints and the key regions in association with the one or more pictures, respectively;
• and
• outputting a table that stores a result of the grouping.

A method of determining picture similarity, comprising:

• deriving a first picture characteristic grouping of a first picture by identifying first key regions in the first picture according to a maximally stable extremal region (MSER) algorithm and calculating first fingerprints respectively corresponding to the first key regions according to a perceptual hash algorithm;
• deriving a second picture characteristic grouping of a second picture by identifying second key regions in the second picture according to the MSER algorithm and calculating second fingerprints respectively corresponding to the second key regions according to the perceptual hash algorithm;
• calculating a hamming distance between the first picture characteristic grouping and the second picture characteristic grouping;
• and
• determining the picture similarity according to the calculated hamming distance.