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

Chinese paper cutting identification method based on space constraint characteristic selection and combination thereof

A feature selection, space constraint technology, applied in the field of image recognition

Inactive Publication Date: 2010-10-06
ZHEJIANG UNIV
View PDF2 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The above two feature extraction methods have certain limitations. Spatial pyramid matching reflects the similarity of images at different scales, and context-dependent histogram reflects the similarity of images with spatial context constraints on the same scale.

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
  • Chinese paper cutting identification method based on space constraint characteristic selection and combination thereof
  • Chinese paper cutting identification method based on space constraint characteristic selection and combination thereof
  • Chinese paper cutting identification method based on space constraint characteristic selection and combination thereof

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach

[0061] After the classification error of each component of the candidate feature V is obtained, it is sorted according to the classification error, and the first Z components with the smallest error in V are selected to form a distinctive feature of the j-th type of paper-cut image. The specific implementation is as follows:

[0062] Input: training sample set S={s k |1≤k≤M}; annotation matrix T={t ij ∈{0, 1}|1≤i≤M, 1≤j≤N}; the feature set to be selected V={v ik |1≤i≤M, 1≤k≤L}

[0063] Output: Z most discriminative components in feature set V

[0064] step:

[0065] 1. Initialize weight W={w ij |1≤i≤M, 1≤j≤N}

[0066] 2. Calculate the arithmetic mean of the sample candidate features C={c k |1≤k≤L}

[0067] 3. Repeat the following operations from k=1 to L:

[0068] a) Calculate:

[0069] FSC ik = 1 if ( sor...

Embodiment 1

[0077] 1) Constructing a paper-cut dataset: 246 Chinese paper-cut images were collected from the Internet. According to these paper-cut art themes, such as figure 2 Shown divides the dataset into four categories: animals, portraits, people, and text. Use 80% of the samples as the training set and 20% as the test set;

[0078] 2) To train the training set samples, the specific steps are as follows:

[0079] a) Preprocess the training set samples, extract SIFT features, and use the K-Means clustering algorithm to extract visual words to form the initial features of the samples;

[0080] b) The method of combining spatial pyramid matching and context-dependent histograms is used to process the initial features of the samples to form candidate features of the samples;

[0081] c) Using AdaBoost-based feature selection and combination technology to process sample candidate features to obtain sample distinguishing features;

[0082] d) Characterize the class by the class center...

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 discloses a Chinese paper cutting identification method based on space constraint characteristic selection and combination thereof, comprising the following steps of: (1) extracting an initial feature of a sample by adopting a method combining space pyramid matching and context dependent histogram to form a candidate feature of the sample; (2) processing the candidate feature by utilizing a feature selection and combination technology based on AdaBoost to obtain a distinctive feature; (3) characterizing the class through the center feature vector of all combination features in each class, the distinctive feature and a distance calculation formula for defining the center feature vector and the distinctive feature; and (4) calculating the distance between the distinctive feature of a testing sample and the center feature of each class to obtain a classification and identification result of paper cutting works. The invention effectively combines the two ways of space pyramid matching and context dependent histogram, overcomes the limitation thereof on expressing the shape of an image, extracts and forms distinctive paper cutting image shape features, and realizes the classification and the identification of paper cutting works on the basis.

Description

technical field [0001] The invention relates to the field of image recognition, in particular to a Chinese paper-cut recognition method based on space-constrained feature selection and combination thereof. Background technique [0002] Paper cutting, also known as "paper carving", is an art that uses paper as the processing object and scissors (or carving knife) as the tool for creation. Paper-cutting has formed a unique art form because of its emphasis on knife skills, exquisite and transparent paper language and emphasis on silhouette modeling. After thousands of years of development and accumulation, paper-cut works can be divided into categories such as animals, portraits, characters and characters. [0003] Paper-cut works contain rich semantics and are difficult to express directly in words. After a large number of paper-cut works have been digitized, in order to take advantage of their sharing, it is urgent to study the search technology for paper-cut works. The Con...

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): G06K9/66
Inventor 邵健庄越挺王霏
Owner ZHEJIANG UNIV
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com