Image analysis method and device based on PCNN model

An image analysis and model technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as poor adaptability of PCNN model, and achieve the effect of improving accuracy

Active Publication Date: 2013-11-27
赵彦明
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the embodiments of the present invention is to provide an image analysis method and device based on the PCNN model to solve the problem of relatively poor adaptability of the above-mentioned PCNN model

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 analysis method and device based on PCNN model
  • Image analysis method and device based on PCNN model
  • Image analysis method and device based on PCNN model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] Hereinafter, the present invention will be described in detail with reference to the drawings and examples. It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0023] Considering that the PCNN model is proposed based on the biological optic neurocortex theory, the network parameters M and W can not only effectively describe the global information of the image, but also describe the change relationship of each pixel relative to the neighboring pixels. Therefore, according to the biological visual information contained in the image itself By setting the network parameters W and M adaptively based on information, the characteristics of the image itself can be accurately described globally and locally. Based on this, an embodiment of the present invention provides an image analysis method and device based on a PCNN model.

[0024] Such as figure 1 Shown is th...

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 an image analysis method and device based on a PCNN model. The image analysis method comprises the steps that a pixel is randomly selected from a current image; the maximum energy of the pixel and corresponding direction channels in adjacent domains is calculated by means of changing the size of a window of a visual information calculation model; the maximum size and effective direction of the visual information calculation model are determined according to the maximum energy of each direction channel; parameters W and M of the PCNN model are determined according to the maximum size and effective direction, wherein the M is a connection matrix of a feedback input domain, and the W is a connection matrix of a coupling connection domain; the current image is subjected to image analysis based on the PCNN model corresponding to the determined W and M. The image analysis method and device based on the PCNN model solve the problem that in the correlation technique, the self-adaptivity of the PCNN model is relatively poor.

Description

technical field [0001] The present invention relates to the field of image processing and analysis, in particular to an image analysis method and device based on a PCNN (Pulse Coupled Neural Networks) model. Background technique [0002] The parameters in the PCNN model can determine the performance of the model in the field of digital image understanding, analysis and pattern recognition. Therefore, various research schemes for setting PCNN network parameters have been proposed in the related art. According to the research content, it can be divided into: 1) Adaptive setting method for one or more parameters of PCNN based on the statistical information of the image; 2) Method for setting parameters of PCNN based on the receptive field; How to set network parameters. [0003] Most of the above PCNN models are parameter settings for images in a specific field, resulting in poor adaptability of the PCNN model. [0004] Aiming at the problem of relatively poor adaptability o...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 赵彦明
Owner 赵彦明
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap