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

A Fast Image Segmentation Method Based on GPU Platform and Morphological Component Analysis for Computer Graphics and Image Processing

A computer graphics and image processing technology, applied in digital image processing and information fields, can solve problems such as low computing efficiency and poor segmentation effect

Inactive Publication Date: 2016-05-18
詹曙 +1
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Purpose of the invention: the technical problem to be solved by the present invention is to propose a fast image segmentation method based on the GPU platform and morphological component analysis, which can effectively reduce the calculation time, Significantly improve the decomposition effect

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
  • A Fast Image Segmentation Method Based on GPU Platform and Morphological Component Analysis for Computer Graphics and Image Processing
  • A Fast Image Segmentation Method Based on GPU Platform and Morphological Component Analysis for Computer Graphics and Image Processing
  • A Fast Image Segmentation Method Based on GPU Platform and Morphological Component Analysis for Computer Graphics and Image Processing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] Step 1. Perform memory allocation optimization and initialization, read the image to be segmented into the CPU memory, and initialize the dictionary matrix, specifically:

[0032] According to the resolution of the input image, the CPU and GPU memory are uniformly allocated and initialized, and no memory allocation is performed until the end of the program; the image to be decomposed is read into the CPU memory, and the dictionary matrix is ​​initialized, using local cosine Transform LDCT to initialize the dictionary D of the texture part of the image t , use the wavelet transform to initialize the dictionary D of the image structure part n ;

[0033] Step 2. Transfer image data and initial dictionary from CPU memory to GPU memory, specifically:

[0034] The image data f to be segmented and the initial dictionary D t 、D n Transfer from CPU memory to GPU memory; assume that image data f contains Gaussian white noise n, and the image can be expressed as f=u+v+n, where...

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 quick image segmentation method used for computer graph and image processing and based on a GPU platform and morphological component analysis. For a traditional image segmentation technology which is low in operation efficiency and poor in segmentation effect, the quick image segmentation method based on the GPU platform and the morphological component analysis is proposed so that operation time can be reduced effectively and the decomposition effect can be improved remarkably. The method includes the implementation steps that due to the fact that the advantages of GPU parallel operation are fully used, the algorithm of the morphological component analysis is achieved, the image segmentation efficiency is improved greatly, and thus quick image segmentation is achieved.

Description

technical field [0001] The present invention relates to the field of information technology, and further relates to a rapid image segmentation using a Graphics Processing Unit (GPU) through a Morphological Component Analysis (MCA) in the field of digital image processing technology. This technology can be widely used in image segmentation, target detection and recognition and other fields. Background technique [0002] An important issue in image processing and computer vision is to distinguish different features of images. The purpose of image segmentation is to separate components with different features in images. Images can be composed of image structure and image texture. Among them, the image structure part contains The geometric feature information of the image consists of smooth regions and clear edges. The texture part of the image is composed of high-frequency oscillation components and noise of the image. In recent years, image segmentation has become a frontier...

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 Patents(China)
IPC IPC(8): G06T1/20G06T7/00
Inventor 詹曙方琪
Owner 詹曙
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