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Feature bag image retrieval method based on Hash binary code

A technology of image retrieval and binary coding, which is used in special data processing applications, instruments, electrical digital data processing, etc.

Active Publication Date: 2016-04-06
NANJING UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

Feature bag image retrieval based on hash binary coding needs to be further improved in terms of performance and accuracy

Method used

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  • Feature bag image retrieval method based on Hash binary code
  • Feature bag image retrieval method based on Hash binary code
  • Feature bag image retrieval method based on Hash binary code

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0133] This embodiment includes the following parts:

[0134] Step 1, build a visual vocabulary:

[0135] Using the k-means method to cluster image features and establish a visual vocabulary, this module is mainly divided into two steps: image feature expression and clustering to establish a visual vocabulary.

[0136] The image feature expression uses the Bag-of-Words (BoW) model.

[0137] The name of the feature bag model comes from the bag-of-words model (Bag-of-Words, BoW) in the field of natural language processing and information retrieval. The bag-of-words model ignores the grammar and word order of the text, and expresses a document with a histogram of unordered words. These words form a dictionary, and the histogram is constructed by counting the number of times the words in the dictionary appear in the document. Usually, words that do not contain information (such as "the") should be removed from the dictionary, and only one item should be used for multiple synony...

Embodiment 2

[0227] Figure 7 The schematic diagram is retrieved for Example 2, and the image source in the figure is the public INRIAHolidays database. In the figure, 1 is the image to be retrieved, 2 is the extracted feature, 3 is the expression of the feature as a vector according to the visual vocabulary, 4 is the projection direction of learning the binary code, and 5 is the feature mapping according to the learned projection direction. 128-bit binary code, 6 is to obtain the retrieval result according to the retrieval score, if the obtained retrieval result and the image to be retrieved belong to the same category, the retrieval is successful.

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Abstract

The invention discloses a feature bag image retrieval method based on a Hash binary code. The method comprises steps that, a vision term list is established; tf-idf (term frequency-inverse document frequency index) weight quantification of vision terms is carried out; vision term characteristic quantification of an image is carried out; an inverted index is established; a feature binary code projection direction is learned; feature binary code quantification is carried out; candidate image sets are retrieved. According to the method, the index is established for an image database, rapid image retrieval is realized, and retrieval efficiency is improved, moreover, through a binary code learning method having the similarity retention capability, the binary code is learned from spatial distance similarity and meaning distance similarity as signature, and image retrieval accuracy is improved. The feature bag image retrieval technology based on the Hash binary code has properties of high efficiency and accuracy, and relatively high use values are realized.

Description

technical field [0001] The invention belongs to the field of image retrieval, in particular to a feature bag image retrieval method based on hash binary coding. Background technique [0002] With the crazy growth of data in the information age, the total amount of image data is also increasing at a high speed, so how to efficiently retrieve image data sets based on hash binary coding has become an important research direction. The methods of image retrieval have also experienced the development from text-based image retrieval (TBIR) which requires manual tagging of keywords to content-based image retrieval (CBIR). And in order to deal with the feature bag image dataset retrieval problem based on hash binary coding more efficiently, a feature bag model retrieval framework is introduced for fast retrieval. In real applications, the image is not so small, and the content contained in the image is also richer. An image file is composed of many local descriptors. [0003] If th...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06K9/62G06F17/30
CPCG06F16/5838G06V10/507G06F18/23213
Inventor 杨育彬朱瑞居振飞毛晓蛟朱启海
Owner NANJING UNIV
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