IMAGE ANALYSIS

摘要

A method for processing an image is proposed. The method comprises identifying a first group of keypoints in the image. For each keypoint of the first group, the method provides for identifying at least one corresponding keypoint local feature related to said each keypoint; for said at least one keypoint local feature, calculating a corresponding local feature relevance probability; calculating a keypoint relevance probability based on the local feature relevance probabilities of said at least one local feature. The method further comprises selecting keypoints, among the keypoints of the first group, having the highest keypoint relevance probabilities to form a second group of keypoints, and exploiting the keypoints of the second group for analysing the image. The local feature relevance probability calculated for a local feature of a keypoint is obtained by comparing the value assumed by said local feature with a corresponding reference statistical distribution of values of said local feature.

主权项

1. A computer for processing an image, the computer comprising:
a memory configured to store computer-readable instructions; and a processor configured to execute the computer-readable instructions stored in the memory to
identify a first group of keypoints in the image;for each keypoint of the first group:
identify at least one corresponding keypoint local feature related to the each keypoint;calculate a corresponding local feature relevance probability for the at least one keypoint local feature; andcalculate a keypoint relevance probability based on the local feature relevance probabilities of the at least one local feature;select keypoints, among the keypoints of the first group, having the highest keypoint relevance probabilities to form a second group of keypoints; andexploit the keypoints of the second group for analyzing the image, wherein the local feature relevance probability calculated for a local feature of a keypoint is obtained by comparing the value assumed by the local feature with a corresponding reference statistical distribution of values of the local feature.