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

Performance analysis method for automatic segmentation result of image

A technology for automatic segmentation and analysis methods, applied in the field of computer vision, can solve problems such as ignoring perceptual consistency

Active Publication Date: 2010-08-11
WUHAN CITMS TECH CO LTD
View PDF5 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This practice ignores the perceptual consistency among the manually annotated segmentation results (5 to 7) in the database

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
  • Performance analysis method for automatic segmentation result of image
  • Performance analysis method for automatic segmentation result of image
  • Performance analysis method for automatic segmentation result of image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The present invention will be described in more detail below by means of examples and drawings, but the following examples are only illustrative, and the protection scope of the present invention is not limited by these examples.

[0040] Such as figure 1 As shown, the specific process is:

[0041] (1) Suppose an image is X={x 1 ,...,x i ,...x N}, consisting of N pixels, x i is the i-th pixel. For the M manually labeled segmentation results of the image, denoted as G={G 1 ,...G k ,...,G M}, usually M takes 5 to 7, and each manual segmentation result is recorded as G k ={R 1 ,...,R j ...,R n}, k ∈ {1,...,M}, which contains n segmentation regions, where each region is denoted as R j , j ∈ {1,...,n}. Then calculate the pixel x i The local consistency degree (Local Consitency Degree), its calculation formula is:

[0042] LCD ( x i ) = max ...

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 performance analysis method for the automatic segmentation result of an image. The method comprises the following steps: enduing each pixel with different weights by calculating the perception uniformity degree among multiple manually-marked segmentation results on the pixels, wherein the higher the perception uniformity degree is, the higher the weight corresponding to the pixel is; and finally calculating a weighted evaluation number as the final evaluation index for the segmentation results to be evaluated. The performance analysis index obtained by the method can quantitatively reflect the uniformity degree between the automatic segmentation result of the image processed by some computer algorithm and the manually-marked segmentation result, thereby objectively reflecting the closeness degree between some computer image automatic segmentation algorithm and the human visual perception in the aspect of image automatic segmentation.

Description

technical field [0001] The invention belongs to the field of computer vision, and in particular relates to a performance analysis method for automatic image segmentation results. Background technique [0002] Image segmentation is an important basic research direction in the field of computer vision. Its purpose is to divide an image into some independent regions, so that in each independent region, the pixels have similar statistical properties, such as grayscale, color, texture etc. Effective image segmentation results will help the subsequent processing in the application system. On the one hand, the category of the scene in the image can be identified by studying the color and texture of each area; The geometric shape of the contour is used to identify or extract objects in the image scene. From the perspective of informatics, processing the segmented image area will greatly reduce the amount of information to be processed compared to directly processing the pixels in ...

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): G06T7/00G06T7/11G06T7/30
Inventor 桑农黄锐唐奇伶王岳环高常鑫高峻
Owner WUHAN CITMS TECH CO LTD
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