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

Blurred image recognition method and apparatus based on SIFT algorithm

A technology of fuzzy images and recognition methods, applied in image enhancement, image data processing, computing, etc., can solve problems such as image effect degradation, image blur, and difficulty in intelligently selecting a series of algorithms

Inactive Publication Date: 2015-09-09
SUZHOU UNIV
View PDF4 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] The blurring causes of blurred images in real life are often very complicated, and most of the current blurred image processing algorithms can only deal with blurred images caused by a certain type of factors. When these algorithms process other images, it is likely to cause the image to go further. the blur
Take the "fogging algorithm" as an example, for those foggy images, the "defogging algorithm" can achieve a good processing effect, but when these algorithms are applied to normal images, the image effect will be degraded
[0014] 3. The empirical nature of the algorithm process
For a specific blurred image, it is difficult to intelligently select the corresponding series of algorithms

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
  • Blurred image recognition method and apparatus based on SIFT algorithm
  • Blurred image recognition method and apparatus based on SIFT algorithm
  • Blurred image recognition method and apparatus based on SIFT algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0154] In this embodiment, the blurred image recognition method based on the SIFT algorithm described in the present invention is used to recognize blurred images caused by various digital noises. Noise-blurred image recognition mainly uses the Gaussian blur subspace in the blur space.

[0155] 1) Gaussian white noise image recognition

[0156] White noise refers to the noise whose power spectral density function is always a fixed value (that is, obeys uniform distribution) in the entire frequency domain range, and its power spectral density function is generally expressed as:

[0157] p ( w ) = n 0 2 ( - ∞ w + ∞ ) . - - - ( 4 - 1 ...

Embodiment 2

[0235] Among the many factors that cause image blur, the influence of illumination factors cannot be ignored. Overexposure or low lighting can have a major impact on image clarity. This embodiment will verify the recognition effect of the SIFT algorithm and the fuzzy image recognition method based on the SIFT algorithm of the present invention on images captured under unfavorable lighting conditions.

[0236] Lighting blur subspace generation

[0237] To identify blurred images caused by lighting factors, the lighting fuzzy subspace in the fuzzy space is mainly used, and the generation process of the lighting fuzzy subspace is used.

[0238] Assuming that the clear image is I, the illuminated blurred image can be obtained by the formula:

[0239] I 2n =F(k 2n (I)). (5-1)

[0240] In the above formula, F(I) represents the operation of performing histogram equalization on the original clear image I, k 2i Is a histogram equalization operation coefficient, used to control th...

Embodiment 3

[0262] During the image capture process, the blurred image generated by the relative motion between the object and the camera is called a motion blur image. Motion blur images widely exist in real life. In this embodiment, the method of the present invention is applied to recognize motion blurred images.

[0263] 1) Motion blur analysis

[0264] Of all types of motion blur, uniform linear motion blur is the most common. Under certain conditions, both non-linear motion and variable speed motion can be regarded as composed of multiple segments of uniform linear motion. In addition, the imaging exposure time is generally very short. During this period, the motion between the object and the camera can be regarded as a uniform linear motion. In this section, the uniform linear motion blur will be analyzed in detail.

[0265] During the camera exposure, the image f(x,y) is assumed to be in uniform linear motion in the image plane. Respectively let x 0 (t) and y 0 (t) represen...

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 present invention relates to a blurred image recognition method and apparatus based on an SIFT algorithm. The method comprises: respectively carrying out Gaussian smoothing, gray level calculation and motion blurring on clear images to generate a fuzzy space; carrying out feature extraction and description on all the images in the fuzzy space based on the SIFT; extracting feature points of a blurred image to be identified by utilizing the SIFT algorithm; respectively matching the feature points of the image to be identified with feature points of each image in the generated fuzzy space; and carrying out estimation on all the matching based on a preset estimating standard, screening an image with the optimal matching effect and using the image with the optimal matching effect as the final recognition result.

Description

technical field [0001] The invention relates to the technical field of fuzzy image recognition, in particular to a fuzzy image recognition method based on the SIFT algorithm. Background technique [0002] Blurred images widely exist in the real world and bring a lot of inconvenience to people's lives. Therefore, the research on blurred images is of great practical significance. After years of development, the correlation processing technology of blurred images has achieved some good applications. From the perspective of image technology, methods related to blurred image processing are mainly divided into three categories: [0003] 1. Image Enhancement [0004] As one of the basic research contents of digital image technology, image enhancement generally enhances information that can meet certain specific needs through certain technical means, and at the same time, may suppress or weaken other information. For a given image, it is necessary to artificially enhance applicat...

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): G06T5/00
Inventor 钟宝江赵帅
Owner SUZHOU 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