The Tape Measurement System Based on Computer Vision Technology

2015 ◽  
Vol 738-739 ◽  
pp. 816-819
Author(s):  
Hong Zhou Li ◽  
Jie Lu ◽  
Jun Wang ◽  
Tao Jia
Keyword(s):  
Computer Vision ◽  
Template Matching ◽  
Vision System ◽  
Median Filter ◽  
Dark Field ◽  
Processing Technologies ◽  
Measurement Results ◽  
System Use ◽  
Dark Field Illumination ◽  
Computer Vision Technology

The paper devises a computer vision system based on virtual instruments to measure tape. The dark field illumination is chosen as Lampe-house in this system. Use Image processing technologies of Median filter, Image binarization, Template matching, Edge extraction to extract a reticle of tape. And compare it with standard tape enacted in this system to measure reticle error of the tape. Analyze various factors influencing the detection precision of the system. Tests show that the measurement results of this system are accurate, reliable and practicable.

Vehicle Security Distance Control Based on Binocular Parallax Vision

2014 ◽  
Vol 644-650 ◽  
pp. 207-210
Author(s):  
Shuang Liu ◽  
Xiang Jie Kong ◽  
Ming Cai Shan
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
High Precision ◽  
Stereo Matching ◽  
Vision System ◽  
Intelligent Transportation ◽  
Distance Control ◽  
Calibration Methods ◽  
Computer Vision Technology ◽  
Vehicle Security

Binocular parallax vision system is a kind of computer vision technology. Two cameras on different locations can get two different pictures of same object. The space position of the object can be calculated by the parallax information of two different pictures. The binocular parallax vision technology includes cameras calibration, image processing, and stereo matching analysis. The paper will introduce the inside and outside parameters calibration methods, and combing the traffic applications, designed the calibrating scheme. The parameters that obtained according to the scheme can meet the demands of measuring the vehicle distance. The high precision can meet the needs of intelligent transportation vehicles in a security vehicles spacing survey, which is an effective way for measuring the front car distance.

The Micro-Indentation Detection of Multilayer Structured Transparent Film Based on Dark Field Illumination

2012 ◽  
Vol 217-219 ◽  
pp. 1043-1048 ◽  
Author(s):  
Jian Kui Chen ◽  
Zhou Ping Yin ◽  
Yong An Huang ◽  
You Lun Xiong
Keyword(s):  
Position Control ◽  
Detection Method ◽  
Vision System ◽  
Dark Field ◽  
Transparent Film ◽  
Experiment Platform ◽  
Roll To Roll ◽  
Dark Field Illumination ◽  
Parallel Strip ◽  
Micro Indentation

It is difficult to keep the precise conveyance in film discontinuous winding system, while there are no etch or print marks on the transparent film. Based on dark field illumination theory, a micro-indentation detection method is proposed for multilayer structured transparent film roll-to-roll processing. Two parallel strip lights are involved in the vision system to illuminate the indentation at a low angle, which ensures that the distinct image of the cutting indentation can be obtained in reflection and diffuse homogeneous lights. The measurement of micro-indentations can be used to evaluate the film conveying positioning accuracy and calculate the compensation of film feeding position control. An experiment platform was established to show the efficiency and feasibility of proposed scheme. Experimental results showed that the micro-indentation detection method, based on dark field illumination, is successful to increase the feeding precision of multilayer structured transparent film discontinuous winding system.

Computer vision-based color sorting for waste textile recycling

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jie Zhou ◽  
Xingxing Zou ◽  
Wai Keung Wong
Keyword(s):  
Computer Vision ◽  
Hong Kong ◽  
Research Methods ◽  
Vision System ◽  
Raw Material ◽  
White Balance ◽  
Content Type ◽  
Textile Recycling ◽  
Computer Vision Technology ◽  
Sorting System

PurposeEfficient and high-accuracy intelligent color and material sorting systems are the main bottlenecks restricting the recycling of waste textiles. The mixing of waste textiles with different colors will make the reconstructed raw material of textile fiber useless or with low quality. In this study, some challenges about the automatic color sorting for waste textile recycling are discussed. A computer vision-based color sorting system for waste textile recycling is introduced, which can classify the required colors well and meet the efficiency requirements of an automatic recycling line.Design/methodology/approachThere are four aspects, (1) two cameras with different exposure times and white-balance parameters are involved for establishing the computer vision system. (2) Two standard color databases with two cameras are constructed. (3) A statistical model to determine the colors of textile samples is presented in which uniform sampling of pixels and mid-tone enhancing techniques are exploited. (4) The experiments with a number of waste textile samples from a factory in Hong Kong are conducted to illustrate the efficiency of the developed system.FindingsThe experiments with a number of waste textile samples from a factory in Hong Kong are reported. The total classification accuracy performs good. The research methods and results reported in this study can provide an important reference for improving the intelligent level of color sorting for waste textile recycling.Originality/valueIt is the first time to introduce computer vision technology to a color sorting system for recycling waste textiles, especially in a real recycling factory in Hong Kong. The research methods and results reported in this study also deliver guidance for designing a computer vision-based color sorting system for other industrial scenarios.

Developments in computer vision system, focusing on its applications in quality inspection of fruits and vegetables-A review

2017 ◽  
Vol 38 (02) ◽  
Author(s):  
Santosh Chopde ◽  
Madhav Patil ◽  
Adil Shaikh ◽  
Bahvesh Chavhan ◽  
Mahesh Deshmukh
Keyword(s):  
Computer Vision ◽  
Fruits And Vegetables ◽  
Vision System ◽  
Cost Effective ◽  
Quality Analysis ◽  
Quality Inspection ◽  
Safety Standards ◽  
Cost Effective Technique ◽  
Recent Developments ◽  
Computer Vision Technology

Quality inspection of food is a tedious and labor intensive process. Ever-increasing population, losses in handling and processing and the increased expectation of food products of high quality and safety standards has raised the need for accurate, fast and objective quality determination methods. Manual quality inspection is a slow, costly, unreliable process and suffers from poor repeatability. Computer vision provides one alternative for an automated, non-destructive and cost-effective technique to accomplish these requirements. Computer vision is a rapid, economic, consistent, objective inspection and evaluation technique. Computer vision has been successfully adopted for the quality analysis of meat and fish, fruits, vegetables and bread with applications ranging from routine inspection to the complex vision guided robotic control. The paper presents the recent developments in computer vision technology along with important aspects of image processing techniques coupled with application of computer vision technology in quality inspection of fruits and vegetables.

ANALYSIS OF METHODS FOR DETECTING FACES IN AN IMAGE

2021 ◽  
pp. 77-88
Author(s):  
Zh. Sultanov
Keyword(s):  
Computer Vision ◽  
Template Matching ◽  
Vision System ◽  
Empirical Method ◽  
Modern Technology ◽  
Detection Methods ◽  
Human Face ◽  
Knowledge Based ◽  
Training Stage ◽  
The Face

In this article, computer vision is considered as modern technology of automatic processing of graphic images, and the relationship between the terms “computer vision” and “machine vision” is investigated. A diagram of a typical computer vision system is given and the possibility of using a system based on an artificial neural network for image analysis is considered. The article analyses the current situation with the use of computer vision systems and the possibility of its application. This article presents face recognition algorithms for existing categories, including: empirical method; feature method – invariant feature; use the template specified by the developer for identification; study the method of detecting the system by external signs. The empirical method of “top-down knowledge-based methods” involves creating an algorithm that implements a set of rules that image segments must satisfy in order to be recognized as faces. Feature-invariant approaches (Feature-invariant approaches) based on bottom-up knowledge constitute the second group of face detection methods. The methods of this group have the ability to recognize faces in different places as an advantage. Use the template set by the developer for identification (template matching method). Templates define specific standard images of face images, for example, describing the attributes of different areas of the face and their possible mutual positions. A method for detecting faces by external signs (a method for performing the training stage of the system by processing test images). The image (or its fragments) is somehow assigned a calculated feature vector, which is used to classify the image into two categories – human face/non-human face.

A computer vision system for objective fabric smoothness appearance assessment with an ensemble classifier

2019 ◽  
Vol 90 (3-4) ◽  
pp. 333-343 ◽  
Author(s):  
Jingan Wang ◽  
Kangjun Shi ◽  
Lei Wang ◽  
Ruru Pan ◽  
Weidong Gao
Keyword(s):  
Computer Vision ◽  
Information Gain ◽  
Vision System ◽  
Objective Assessment ◽  
Ensemble Classifier ◽  
Image Feature ◽  
Support Vector ◽  
Computer Vision System ◽  
Processing Technologies ◽  
Feature Sets

Fabric smoothness appearance assessment plays an important role in the textile and apparel industry. To evaluate fabric smoothness objectively, different methods have been proposed based on computer vision technology. To further improve the performance and promote the application of the assessment methods, this paper reports a hybrid computer vision system for objective assessment of fabric smoothness appearance with an ensemble classifier to integrate the advantages of the different image feature sets, which are extracted based on different image processing technologies. The image acquisition environment is established in this system with the selection of illumination parameters—intensity, position angle and altitudinal angle—by a designed strategy. The main steps of the strategy include determination of priority by information gain analysis and parameter selection by classifier performance analysis. The support vector machine classifiers trained by each feature sets are grouped into an ensemble by a self-adapting weighted voting method and the redundant feature sets are eliminated based on the weights of the feature sets. The final result shows evaluation accuracies with 82.86% under 0-degree error, 97.14% under 0.5-degree error and 100% under 1-degree error, which outperforms the other methods in the same environment and verifies the applicability of the proposed system.

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

scholarly journals A Review on Computer Vision Technology for Monitoring Poultry Farm – Application, Hardware, and Software

IEEE Access ◽  
2020 ◽  
pp. 1-1
Author(s):  
Nur Syazarin Natasha Abd Aziz ◽  
Salwani Mohd Daud ◽  
Rudzidatul Akmam Dziyauddin ◽  
Mohamad Zulkefli Adam ◽  
Azizul Azizan
Keyword(s):  
Computer Vision ◽  
Poultry Farm ◽  
Computer Vision Technology

scholarly journals Measurement of Gem Colour Using a Computer Vision System: A Case Study with Jadeite-Jade

Minerals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 791
Author(s):  
Sufei Zhang ◽  
Ying Guo
Keyword(s):  
Computer Vision ◽  
Regression Model ◽  
Vision System ◽  
Expert Group ◽  
Group Test ◽  
System A ◽  
Real Objects ◽  
Practical Tool ◽  
Almost All

This paper introduces computer vision systems (CVSs), which provides a new method to measure gem colour, and compares CVS and colourimeter (CM) measurements of jadeite-jade colour in the CIELAB space. The feasibility of using CVS for jadeite-jade colour measurement was verified by an expert group test and a reasonable regression model in an experiment involving 111 samples covering almost all jadeite-jade colours. In the expert group test, more than 93.33% of CVS images are considered to have high similarities with real objects. Comparing L*, a*, b*, C*, h, and ∆E* (greater than 10) from CVS and CM tests indicate that significant visual differences exist between the measured colours. For a*, b*, and h, the R2 of the regression model for CVS and CM was 90.2% or more. CVS readings can be used to predict the colour value measured by CM, which means that CVS technology can become a practical tool to detect the colour of jadeite-jade.

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