System and method for recognizing different defect types in paper defect visual detection

A technology for visual inspection and defect types, which is applied in the field of systems for identifying different defect types, and can solve problems such as increasing the difficulty of inspection and difficulty in real-time processing by PCs and industrial computers.

Inactive Publication Date: 2011-06-15
QILU UNIV OF TECH
View PDF0 Cites 31 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, due to the many types of paper defects, the difficulty of detection is increased, making defect detection one of the difficulties in the entire monitoring system, and has become a bottleneck in the practicability and accuracy of the paper monitoring system.
[0004] In view of the high requirement of real-time performance, general-purpose PCs and industrial computers are difficult to meet the requirements of real-time processing, which requires a dedicated fast image processing chip to be used in this field

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
  • System and method for recognizing different defect types in paper defect visual detection
  • System and method for recognizing different defect types in paper defect visual detection
  • System and method for recognizing different defect types in paper defect visual detection

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0052] A total of 100 images of typical defects collected by the camera, mainly including broken edges, holes, folds, grass fibers and some relatively rare defects, were tested and analyzed with 100 images without defects. Such as Figure 4 Shown in are images with various paper defects and images without defects. A certain number of defective images and non-defective images are randomly selected from the above images as training samples for training, and the rest are used as test samples for training and identification based on the SVM method. The overall test results are shown in Table 1. In order to highlight the superiority of this algorithm In order to improve the performance, artificial neural network algorithm was used to test under the same conditions, and the results are shown in Table 2. At the same time, the kernel parameters of the SVM algorithm are changed, and the corresponding results are shown in Table 3.

[0053] Experimental steps:

[0054] Step 1, use thi...

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 relates to a system and a method for recognizing different defect types in paper defect visual detection. The system and the method have high recognition rate and high speed, and can recognize different defect types in paper defect visual detection with the average recognition rate of 97.5% and false recognition rate of 2.5%, thereby substantially achieving exhaustive detection and recognition of defective images. The time for entire defect recognition process is less than 10 ms, and can substantially meet the time requirement for paper real-time detection under the actual production conditions. The system comprises an image pickup device matching with the paper sheet to be detected, and a light source matching with the paper sheet to be detected, wherein the image pickup device is connected with an image capture card; the image capture card transmits the obtained image to a computer and a DSP (digital signal processor) image processing unit; and the DSP image processing unit is connected with the computer.

Description

technical field [0001] The invention relates to a DSP-based paper defect detection system, in particular to a system and method for identifying different defect types in visual detection of paper defects. Background technique [0002] Although we have now entered the information age, the status of paper as an information carrier has not changed. As the main substrate in the printing industry, the influence of paper quality on the quality of printed matter cannot be ignored. High-quality paper can reduce the impact on the printing process and obtain more satisfactory printed products. At present, the common paper defects mainly include folds, clear spots, holes, holes, dust, etc. For high-grade paper and specialty paper used for packaging and printing, these appearance paper defects are one of the main factors affecting product quality. If the paper or cardboard has paper defects, it will not only affect the printing effect and hinder writing, but also reduce the strength o...

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): G01N21/88G06K9/66
Inventor 邱书波王磊杨秀蔚
Owner QILU 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