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Post-verification method for local feature point matching pairs

A technology of local features and verification methods, applied in computer parts, special data processing applications, instruments, etc., can solve problems such as weakened discrimination ability and reduced matching accuracy, and achieves improved accuracy, high accuracy, and good robustness. sexual effect

Active Publication Date: 2017-07-28
HANGZHOU DIANZI UNIV
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  • Claims
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AI Technical Summary

Problems solved by technology

[0005] Aiming at the problem of reduced matching accuracy caused by the weakening of distinguishing ability after local features are quantized into visual words, the method of the present invention proposes to use the attribute change consistency between local feature point matching pairs and a voting method to confirm the correct match right

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  • Post-verification method for local feature point matching pairs
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  • Post-verification method for local feature point matching pairs

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Embodiment Construction

[0042] The present invention will be described in detail below in conjunction with the accompanying drawings. It should be noted that the described embodiments are only for understanding of the present invention, and do not limit it in any way.

[0043] The concrete steps of the inventive method are:

[0044] Step (1) Obtain the matching pair of local feature points in the two images according to the visual vocabulary corresponding to the local feature points; there are currently many methods for extracting the local feature points, and the method of the present invention adopts the currently widely used scale-invariant descriptor ( SIFT), which is robust to rotation and scale transformation. After the SIFT descriptor is extracted, the image is represented as a set of local feature points {S i},S i is a local feature point descriptor in the image, which has the following related attributes in the image: feature vector (F i ), the main direction (θ i ), scale (σ i ), and s...

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Abstract

The invention discloses a post-verification method for local feature point matching pairs. The method includes the steps of firstly, extracting local feature points in an image, and obtaining candidate local feature point matching pairs through visual vocabulary; then, extracting attribute changing values from the candidate local feature point matching pairs: a main direction changing value and an azimuth changing value; next, verifying whether two matching pairs are consistent according to the attribute changing values of the matching pairs and a threshold value; and finally, determining whether the candidate local feature point matching pairs are correct based on the number of affirmative votes using a voting algorithm. The post-verification method can be adapted to the influence brought by image cutting, rotation, scale-zooming and other transformation and can be applied to image retrieval, classification and the like based on the visual vocabulary to improve the accuracy of retrieval and recognition. The post-verification method of the invention has a very good verification effect for feature point matching pairs in those non-perspective transform images, and can greatly improve the accuracy and recall rate of copy retrieval in the application of image copy retrieval based on the visual vocabulary.

Description

technical field [0001] The invention belongs to the field of computer image processing and image retrieval, and relates to a post-verification method for matching pairs of local feature points in two images. Background technique [0002] With the extensive research and application of local feature points in images, image analysis, recognition and retrieval based on local feature points has become an important way in the current image processing field. Referring to the bag-of-words model in document processing, an image can be represented as a collection of local features, thereby eliminating some redundant information in the image. In recent years, researchers have quantified the descriptors of local feature points into visual words, thus proposing the Bag of visual words model. This model has become an important method of image recognition and retrieval. The combination of visual vocabulary bag-of-words model and inverted index is currently the most effective content-base...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06F17/30
CPCG06F16/583G06V10/757
Inventor 姚金良
Owner HANGZHOU DIANZI UNIV
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