Method and system for extracting image fingerprints based on representative local mode

Abstract

The invention discloses a method and system for extracting image fingerprints based on a representative local mode, and relates to the field of image processing. The method comprises: performing image attack analog processing of database images to generate new database images; extracting key points of the database images and the new database images; obtaining local blocks according to the key points; generating local modes and establishing a local mode database according to the local blocks; obtaining the representative local mode from the local mode database; establishing image fingerprints of the database images and the new database images according to the representative local mode; storing the image fingerprints into an image fingerprint database; obtaining a new image and extracting fingerprints of the new image; comparing the fingerprints of the new image with the image fingerprints in the image fingerprint database; and searching an image corresponding to the new image in the database images. According to the invention, the required memory is small; accelerated matching is performed by using an optimized machine instruction; the method and system are suitable for massive image copying and detection.

Description

technical field

[0001] The invention relates to the field of image processing, in particular to an image fingerprint extraction method and system based on representative local patterns. Background technique

[0002] Image copy detection has always been one of the hot research areas of computer vision. Its general strategy is to extract a few features from the image and integrate them into a feature vector that can reflect the content of the image. From the perspective of the composition of image features, it is generally divided into global features and local features. The following is a brief discussion of the development status of these two features. As early as 1999, Naphade was the first method to extract the histogram of the image in the LUV color space as an image signature, and then Mohan used the block method to extract the average gray value of each block, according to the gray value of these blocks Size sorting construction features; a relatively influential image...

Examples

Embodiment Construction

[0042] The present invention proposes a method for extracting image fingerprints based on representative local patterns, the specific process of which is as follows: figure 1 As shown, the main process of the present invention is divided into three stages: training stage, database building stage and online query stage. The three stages include image preprocessing, which is mainly to unify and smooth the size of the original image. The main steps of the three stages are introduced below:

[0043] Training stage: This stage is mainly to perform various image attack simulation processing on the library image, mainly including scale change, subtitle or logo embedding, cropping, blurring, etc., and then use the FAST algorithm to extract key points in the image, (“key point” refers to The most important thing is the local structure that contains important information in the image. For example, the eyes and nose of the face are more prominent than the forehead and contain more inform...

technical field

[0001] The invention relates to the field of image processing, in particular to an image fingerprint extraction method and system based on representative local patterns. Background technique

[0002] Image copy detection has always been one of the hot research areas of computer vision. Its general strategy is to extract a few features from the image and integrate them into a feature vector that can reflect the content of the image. From the perspective of the composition of image features, it is generally divided into global features and local features. The following is a brief discussion of the development status of these two features. As early as 1999, Naphade was the first method to extract the histogram of the image in the LUV color space as an image signature, and then Mohan used the block method to extract the average gray value of each block, according to the gray value of these blocks Size sorting construction features; a relatively influential image...

Examples

Embodiment Construction

[0042] The present invention proposes a method for extracting image fingerprints based on representative local patterns, the specific process of which is as follows: figure 1 As shown, the main process of the present invention is divided into three stages: training stage, database building stage and online query stage. The three stages include image preprocessing, which is mainly to unify and smooth the size of the original image. The main steps of the three stages are introduced below:

[0043] Training stage: This stage is mainly to perform various image attack simulation processing on the library image, mainly including scale change, subtitle or logo embedding, cropping, blurring, etc., and then use the FAST algorithm to extract key points in the image, (“key point” refers to The most important thing is the local structure that contains important information in the image. For example, the eyes and nose of the face are more prominent than the forehead and contain more inform...

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