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Graphic retrieval method

A graphics and retrieval system technology, applied in the field of information retrieval, can solve the problems of poor robustness, large influence of subjective judgment, and high missed detection rate, so as to eliminate wrongly matched graphics, good robustness, and low missed detection rate. Effect

Active Publication Date: 2018-11-06
南昌奇眸科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem solved by the present invention is: the existing graphic retrieval method is greatly affected by subjective judgment, or the graphic feature description and similarity measurement method adopted cannot retrieve the expected results, and the missed detection rate is high and the robustness is poor

Method used

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Examples

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Embodiment 1

[0044] To be retrieved trademark graphic A w×h For example, w and h represent the width and height of the graphic respectively, and the retrieval method of the present invention is used for retrieval.

[0045] First input the graph to be retrieved, and then perform multi-scale feature extraction. The specific steps are as follows:

[0046] 1. Customize the specification and sliding step of the multi-scale sliding window. The specification of the sliding window is shown in Table 1. The sliding step μ is 0.1, the horizontal step of the sliding window is 0.1w, and the vertical step of the sliding window is 0.1 h.

[0047]

[0048] Table 1. Specifications of multi-scale sliding windows

[0049] 2. Use the sliding window defined in step 1 as graph A w×h Starting from the upper left corner of , according to the horizontal sliding step and vertical sliding step, slide from left to right and from top to bottom in turn to obtain a system of window image sets R of different sizes,...

Embodiment 2

[0090] The difference between this embodiment and Embodiment 1 is that the specification of the sliding window and the sliding step are different, see Table 2 for the specific specification, and the horizontal and vertical sliding steps of the sliding window are 0.2w and 0.2h respectively. The feature window matching between global scales uses the Euclidean distance to calculate the similarity distance d, d min-i sim (T sim =0.3), mark the pair of feature windows.

[0091]

[0092] Table 2. Specifications of multi-scale sliding windows

[0093] attached image 3 The retrieval results of this embodiment are given, wherein, the graph 000000 is the input graph to be retrieved, and the graphs 000001-000009 are the retrieval results.

Embodiment 3

[0095] The difference between this embodiment and Embodiment 1 is that the specification of the sliding window and the sliding step are different, see Table 3 for the specific specification, and the horizontal and vertical sliding steps of the sliding window are 0.1w and 0.2h respectively. The feature window matching between global scales uses the Hamming distance to calculate the similarity distance d, d min-i sim (T sim =0.5), mark the pair of feature windows.

[0096]

[0097] Table 3. Specifications of multi-scale sliding windows

[0098] attached Figure 4 The retrieval results of this embodiment are given, wherein, the graph 000000 is the input graph to be retrieved, and the graphs 000001-000009 are the retrieval results.

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Abstract

The invention relates to the field of information retrieval and in particular to a graphic retrieval method. The graphic retrieval method provided by the invention comprises the following steps of (1)inputting a graphic into a retrieval system; and (2) enabling the retrieval system to perform graphic feature analysis specifically including the step of performing multi-scale feature extraction onthe input graphic and all graphics in the retrieval system to obtain a feature of each window; and then, performing matching between a to-be-retrieved graphic window and a system graphic window according to the features, first performing matching between global inter-scale feature windows, then screening matches of which scale-spaces are consistent, further segmenting similar regions according toa self-adaptive threshold value, and at last performing matching between local feature windows in the similar regions to obtain a final retrieval result. The graphic retrieval using the method is simple, rapid, low in omission ratio and good in robustness.

Description

technical field [0001] The invention relates to the field of information retrieval, in particular to a method for graph retrieval, in particular to a method for graph retrieval by extracting histogram features of multi-scale sliding windows and matching feature windows between scales. Background technique [0002] With the rapid development of science and technology, the popularity of computers and information networks, the amount of various information data is growing at an alarming rate. How to conveniently, accurately and efficiently obtain the required information from the huge information data has become the focus of people's attention. There is a large amount of image information on major social platforms and e-commerce platforms, and image retrieval has become a common retrieval method. Image retrieval can be divided into two categories according to the different ways of describing image content, one is text-based image retrieval (TBIR, Text Based Image Retrieval), a...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06K9/46G06K9/62
CPCG06V10/507G06V10/751
Inventor 樊晓东李建圃
Owner 南昌奇眸科技有限公司
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