Semantic-based image adaptive method by combination of slit cropping and non-homogeneous mapping

A technology of non-uniform mapping and slit cutting, applied in the field of image processing, can solve the problems of immature foreground and background classification technology and limitations in popularization and application

Inactive Publication Date: 2010-12-22
BEIJING UNIV OF TECH
View PDF3 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The bottleneck of this type of method is that the universal object segmentation technology and the robust foreground and b...

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
  • Semantic-based image adaptive method by combination of slit cropping and non-homogeneous mapping
  • Semantic-based image adaptive method by combination of slit cropping and non-homogeneous mapping
  • Semantic-based image adaptive method by combination of slit cropping and non-homogeneous mapping

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0056] The technical solution of the present invention will be described in more detail below with reference to the drawings and embodiments.

[0057] The overall process of the technical solution is shown in the attached figure 1 As shown, this embodiment is carried out for the basketball video in the sports video, and the frame size of the source basketball image is a BMP bitmap of 288*352 pixels. Combined with the semantic analysis results of the middle layer of sports video, the statistical features of the user's subjective evaluation of the importance of semantic regions are extracted for image frames, and are used to weight the energy function based on the underlying features to obtain a semantically weighted energy function. Next, use the forward energy slit cutting method to remove unimportant information in the image, and at the same time use the change of important semantic edges to measure the deformation of important information. When the deformation exceeds the se...

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 semantic-based image adaptive method by combination of slit cropping and non-homogeneous mapping, comprising the following steps: by combining with a semantic analysis result of an intermediate layer of a sports video, extracting statistical characteristics for subjective evaluation on semantic region importance of a user for an image frame, and weighing an underlying feature-based energy function through the statistical characteristics to obtain the energy function after semantic weighing; removing unimportant information in images by using a slit cropping method for positive energy, and meanwhile measuring important information deformation according to variation of an important semantic edge; and when deformation exceeds a set index, terminating the slit cropping method, and using a non-homogeneous mapping method to obtain the images of a target size, wherein, a method framework is as shown in an attached figure of an abstract. The semantic-based image adaptive method organically combines the existing two relatively good methods-the slit cropping method and the non-homogeneous mapping method, gives full play to respective advantages to achieve a comprehensive optimum image video adaptive result, and introduces energy function calculation after semantic weighing to achieve adaptive image sizes based on the semantic content.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to the research and realization of an image self-adaptive method based on the combination of semantic-based thin seam cutting and non-uniform mapping. Background technique [0002] With the popularity of mobile devices, terminal devices suitable for different networks such as TVs, notebook computers, PDAs, and mobile phones are constantly being updated, and display terminals of different types and sizes are emerging to meet various user needs. In order to ensure that users with different devices can watch the same image content comfortably, it is required that the image content can be adapted to user terminals of different sizes and proportions. It is of great application significance to study the adaptive technology that keeps the main content of the image. [0003] At present, the main image size adaptive methods include linear deformation (Scaling) method, cropping (Crop...

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): G06T1/00G06T7/00
Inventor 毋立芳宫玉邓亚丽刘书琴王红
Owner BEIJING UNIV OF TECH
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