Image processing method, apparatus and storage medium

An imaging processing apparatus, comprising:

• a processor;
• and
• a memory storing processor executable instructions;
• wherein the processor is configured to invoke the processor executable instructions stored in the memory to:
• according to first features of a plurality of first images to be processed, determine respectively a density of each of the first features, wherein the density of a first feature represents a number of first features whose distance from said first feature is less than or equal to a first distance threshold;
• determine density chain information corresponding to a target feature according to the density of the target feature, wherein the target feature is any one of the first features;
• the density chain information corresponding to the target feature includes N features;
• an ith feature of the N features is one of first nearest neighbor features of an (i−1)th feature of the N features, and the density of the ith feature is greater than the density of the (i−1)th feature;
• N and i are positive integers, and 1<i≤N;
• the first nearest neighbor features include at least one first feature whose distance from the (i−1)th feature is less than or equal to a second distance threshold, and the target feature is a first one of the N features;
• adjust respectively each of the first features according to the density chain information corresponding to each of the first features, to obtain second features of the plurality of first images;
• and
• cluster the second features of the plurality of first images to obtain a processing result of the plurality of first images.

A non-transient computer readable storage medium storing computer program instructions, wherein the computer program instructions, when executed by a processor, cause the processor to:

• according to first features of a plurality of first images to be processed, determine respectively a density of each of the first features, wherein the density of a first feature represents a number of first features whose distance from said first feature is less than or equal to a first distance threshold;
• determine density chain information corresponding to a target feature according to the density of the target feature, wherein the target feature is any one of the first features;
• the density chain information corresponding to the target feature includes N features;
• an ith feature of the N features is one of first nearest neighbor features of an (i−1)th feature of the N features, and the density of the ith feature is greater than the density of the (i−1)th feature;
• N and i are positive integers, and 1<i≤N;
• the first nearest neighbor features include at least one first feature whose distance from the (i−1)th feature is less than or equal to a second distance threshold, and the target feature is a first one of the N features;
• adjust respectively each of the first features according to the density chain information corresponding to each of the first features, to obtain second features of the plurality of first images;
• and
• cluster the second features of the plurality of first images to obtain a processing result of the plurality of first images.