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

Bayesian Decision Theory foreground extraction method combined with reflected illumination

A foreground extraction and Bayesian technology, applied in image data processing, instrumentation, computing, etc., can solve problems such as unsatisfactory results, achieve fast segmentation speed, increase accuracy, and continuous edge segmentation

Active Publication Date: 2013-06-19
SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
View PDF2 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although this method is faster, the effect is not ideal

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
  • Bayesian Decision Theory foreground extraction method combined with reflected illumination
  • Bayesian Decision Theory foreground extraction method combined with reflected illumination
  • Bayesian Decision Theory foreground extraction method combined with reflected illumination

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] A preferred embodiment of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0029] S1. grayscale matching transformation

[0030] a) Input the image, and the user specifies one or several intensities on the foreground layer as LA point light source, a point on the image surface P The resulting luminance , ρ is the BRDF (Bidirectional Reflectance Distribution Function) of the surface under a given illumination and viewing angle, r is the distance from the light point, θ is the angle between the light point and point P. The foreground layer is farther away from the light point, so the foreground objects will have a larger change in exposure, while the background objects will change less.

[0031] b) According to the luminance change calculated after the user input, set the histogram after matching transformation, and specify the probability density on the corresponding gray level for the specified h...

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 provides a Bayesian Decision Theory foreground extraction method combined with reflected illumination. The Bayesian Decision Theory foreground extraction method comprises the steps of appointing a point light source located on a foreground object by a user, carrying out gray level matching on an image, converting and imitating point light source illumination, strengthening image edge information, obtaining an illumination function according to before-after conversion comparison, filtering waves, reducing noise, dividing the image through a watershed algorithm, calculating a sectional drawing parameter through a Bayes formula, imitating an alpha value function curve through a multi-layer perception device, integrating the illumination function and a color distribution function, and completing extraction of the foreground object. The user is only required to appoint the position of the point light source and not required to preset edge information of a foreground and a background, the requirement for user interaction is reduced, meanwhile, time complexity of the used algorithms is series, and the defects that a common sectional drawing algorithm is large in calculated quantity and low in processing speed are avoided. Due to the facts that the illumination function is introduced and the alpha value is matched by the perception device, an accurate and complete extraction result can be obtained for the foreground object with complicated edges, and particularly for the foreground object similar colors of the edge and the ground.

Description

technical field [0001] The invention belongs to the technical field of computer image processing, in particular to a Bayesian decision-making foreground extraction method combined with reflected light. Background technique [0002] The foreground extraction technology is a method of specifying a small number of foreground and background areas in an image by the user, and automatically and accurately separating all foreground objects according to certain judgment rules according to these prompts. [0003] Foreground extraction technology is an indispensable key technology in film and television production, and is widely used in media production. Today, many different algorithms have been produced: Rotoscoping method, Autokey method, Knockout method, Ruzon-tomasi method, Hillman method, Bayesian method, Poisson method, Grabcut method, Lazy snapping and matting based on perceptual color space method and so on. Foreground extraction in natural images can be divided into region...

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): G06T7/00G06T5/00
Inventor 王好谦邓博雯邵航戴琼海
Owner SHENZHEN GRADUATE SCHOOL TSINGHUA 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