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Real-time vision frequency and image abstraction method based on characteristic

An abstraction and image technology, applied in the direction of image enhancement, image data processing, instruments, etc., can solve the problems of hard and incoherent extraction lines, and achieve the effect of solving the blunt extraction of lines

Inactive Publication Date: 2008-10-15
ZHEJIANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method adopts an anisotropic Gaussian difference line extraction technology based on feature flow, which effectively solves the problem of hard and incoherent extraction lines existing in the existing multi-real-time video and image abstraction methods

Method used

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  • Real-time vision frequency and image abstraction method based on characteristic
  • Real-time vision frequency and image abstraction method based on characteristic
  • Real-time vision frequency and image abstraction method based on characteristic

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Embodiment Construction

[0030] An embodiment of a feature-based real-time video and image abstraction method of the present invention will be described in detail below with reference to the accompanying drawings.

[0031] Such as figure 1 As shown, a feature-based real-time video and image abstraction method, including converting the original red, green and blue color space of each frame image in the real-time video and image sequence to the CIE-Lab color space, using a bilateral grid Perform fast bilateral filtering on the brightness channel, pseudo-quantize the brightness value, use the anisotropic Gaussian difference line extraction algorithm based on the feature flow to extract the line area, and perform a combined operation on the extracted line area and the pseudo-quantized approximate brightness value to make the line There are five steps to enhance the lines of the area and convert the image from the CIE-Lab color space back to the red, green and blue color space.

[0032] The five steps of ...

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Abstract

The invention discloses a feature-based real-time video image abstraction method, which comprises five steps of converting RGB color space of the real-time videos and images into CIE-Lab color space, adopting a bilateral grid to carry out the rapid bilateral filtering of a brightness channel, carrying out the pseudo-quantization of the brightness value, adopting the feature-flow-based anisotropic Gaussian differential line to extract the algorithm extraction line region and carry out the combined operation of the extracted line region and the similar brightness value to strengthen the lines of the line region and re-converting the real-time videos and images to the RGB color space from the CIE-Lab color space. Each step of the invention can be parallelly processed in a graphics card hardware of a household computer, thus effectively solving the rigid and incoherent problems of the extracted lines in the existing abstraction method of multiple real-time videos and images, and providing the simple, convenient, intuitive and real-time video and image abstraction method for non-professionals.

Description

technical field [0001] The invention relates to the technical field of computer image and video processing, in particular to a feature-based real-time video and image abstraction method. Background technique [0002] Real-time video and image abstraction provides a simple, fast, and beautiful visual communication tool by simplifying low-contrast areas and enhancing high-contrast areas. [0003] When artists want to paint a scene, they don't just paint all the visual information in the scene. Instead, they select only the important information and use their imagination to display it. Lines can describe information effectively and naturally, and have been used by humans for tens of thousands of years. In recent years, abstraction techniques have become more and more popular because they can make images and videos easier to understand, see D. Decarlo and A. Santella. Stylization and Abstraction of Photographs. In Proceedings of the ACM SIGGRAPH, 2002, pp 769- 776. [0004] ...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 赵汉理金小刚
Owner ZHEJIANG UNIV
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