Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Image retrieval method and image retrieval device

An image retrieval and image technology, applied in the field of computer vision, can solve problems such as inaccurate retrieval results, achieve the effects of strong ease of use and practicability, simple implementation, and reduced product cost

Active Publication Date: 2014-05-14
深圳市弘志拓新创业投资企业(有限合伙)
View PDF3 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present invention is to provide an image retrieval method and device to solve the problem that the retrieval results of the existing text-based image retrieval technology are not accurate enough

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Image retrieval method and image retrieval device
  • Image retrieval method and image retrieval device
  • Image retrieval method and image retrieval device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] figure 1 The implementation flow of the image retrieval method provided by the first embodiment is shown, and the process of the method is described in detail as follows:

[0031] In step S101, the feature points of each image in the image set are extracted to form a feature point library.

[0032] In this embodiment, in order to obtain more feature points and improve the accuracy of image retrieval, the feature points are preferably scale-invariant feature transform (Scale-invariant feature transform, SIFT) feature points.

[0033] Wherein, the feature points of each image in the extracted image set specifically include:

[0034] For each image in the image set, map all its SIFT feature points to N classes according to the minimum distance principle to obtain an N-dimensional feature vector V1, divide each value in V1 by the total number of feature points in the image to obtain a frequency feature vector V2 and V2 are the SIFT feature points of the image.

[0035] I...

Embodiment 2

[0050] Figure 6 The composition structure of the image retrieval device provided by the second embodiment of the present invention is shown, and for the convenience of description, only the parts related to the embodiment of the present invention are shown.

[0051] The image retrieval device can be applied to various terminal devices, such as pocket computers (Pocket Personal Computer, PPC), palmtop computers, computers, notebook computers, personal digital assistants (Personal Digital Assistant, PDA), etc., and can be run in these terminals The software unit, hardware unit or a combination of software and hardware can also be integrated into these terminals as an independent pendant or run in the application systems of these terminals.

[0052] The image retrieval device includes a feature point extraction unit 61 , a clustering unit 62 , a class prediction unit 63 , a counting unit 64 , a score calculation unit 65 and a result output unit 66 . Among them, the specific fun...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention is applicable to the field of computer vision, and provides an image retrieval method and an image retrieval device. The method includes extracting feature points of each image in an image set to create a feature point library; clustering the feature points in the feature point library to acquire N category, wherein the N is pre-defined as an integer larger than 0; extracting feature points of a to-be-retrieved image, predicating category of the to-be-retrieved image according to the feature points of the to-be-retrieved image, wherein the category is one of the N category; counting the occurrence frequency of N-category feature points in the to-be-retrieved image to acquire front M-category feature points with highest occurrence frequency, wherein the M is an integer larger than 0 but smaller than N; acquiring an image set corresponding to the category, counting the occurrence frequency of the M-category feature points in each image of the image set, and summing up the occurrence frequency to acquire values; outputting front L images with highest values, wherein the L is an integer larger than 0. By the image retrieval method and the image retrieval device, image retrieval results can be acquired rapidly and accurately.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to an image retrieval method and device. Background technique [0002] Image retrieval refers to finding image processing techniques that have specified characteristics or contain specified content in an image collection. With the continuous development of multimedia technology, network technology and database technology, and the continuous popularization of the Internet, people's demand for multimedia data such as graphics and images is becoming stronger and stronger, so the application of image information is becoming more and more extensive. The capacity of digital images is growing rapidly with people's needs, and millions of images are generated every day. Therefore, it will be very necessary to provide a fast and accurate image retrieval technology. [0003] The existing image retrieval technology is mainly text-based image retrieval. The essence of this ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F17/30G06K9/46
CPCG06F16/5838
Inventor 刘宇冯良炳
Owner 深圳市弘志拓新创业投资企业(有限合伙)
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products