Realization Method of Discriminating Binary Image Feature Similarity Based on Random Forest Algorithm

A random forest algorithm, binary image technology, applied in computing, computer parts, character and pattern recognition, etc., can solve the problem of lack of accurate matching, and achieve the effect of improving retrieval speed, matching speed, and average retrieval accuracy.

Active Publication Date: 2019-03-01
XI AN JIAOTONG UNIV
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  • Application Information

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Problems solved by technology

Most of the current research is only carried out to the setting matching of the threshold, and there is no supervised exact matching for the features after the threshold matching.

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  • Realization Method of Discriminating Binary Image Feature Similarity Based on Random Forest Algorithm
  • Realization Method of Discriminating Binary Image Feature Similarity Based on Random Forest Algorithm
  • Realization Method of Discriminating Binary Image Feature Similarity Based on Random Forest Algorithm

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Embodiment Construction

[0028] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0029] In the offline indexing stage, the features in the image library are extracted, and the feature library is established; in the online retrieval stage, the features of the query image are extracted, matched with the features in the feature library, and the matched features are input into the random forest discriminant model. Voting mechanism, output retrieval results.

[0030] see figure 1 , the present invention is based on random forest algorithm to distinguish binary image characteristic similar realization method, comprises the following steps:

[0031] 1) In the offline indexing stage, the scale-invariant feature conversion feature of the image is extracted, each dimension of all features is regarded as a vector and clustered with the K-means method to obtain 5 cluster centers, and then the scale-invariant feature conversion feature...

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Abstract

The invention discloses a method for realizing the similarity of discriminative binary image features based on the random forest algorithm. The method includes: in the offline indexing stage, extracting the scale-invariant feature conversion features of the image, and treating each dimension of all features as a vector with K The mean value method is used for clustering, and the scale-invariant feature conversion feature is quantized into a 512-dimensional binary feature; the quantized feature, feature index, image name corresponding to the feature, and its neighbor features are written into the database as an image feature library. In the online retrieval stage, extract the scale-invariant feature conversion feature of the image, quantize the feature into a 512-dimensional binary feature, and match it with the feature in the image feature library, find out the feature's neighbor feature, and use the random forest algorithm to distinguish the neighbor feature , the voting mechanism retrieves similar images.

Description

Technical field: [0001] The invention relates to similar image retrieval in the technical field of image processing, in particular to a method for realizing the similarity of distinguishing binary image features based on a random forest algorithm. Background technique: [0002] With the rapid development of Internet technologies such as big data and cloud computing, image files and related materials stored on the Internet have increased rapidly. At present, there are hundreds of millions of Internet images. How to store these large-scale Quickly and accurately retrieving the pictures that users want from the image database has become an important research direction in the field of computer vision. [0003] Traditional image retrieval models such as Bag of Words (BoW) and Local Aggregation Vectors (VLAD), when indexing images offline, first cluster the features of the image, the cluster centers are used as visual words, and then the features are quantized into visual words. ...

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Application Information

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Patent Type & AuthorityPatents(China)
IPC IPC(8): G06K9/46G06K9/62G06K9/66G06F16/532
CPCG06F16/583G06V10/462G06V30/194G06F18/23213
Inventor王霞王珊马涛
OwnerXI AN JIAOTONG UNIV