A Double Image Acquisition System with Visible and UV LEDs for Citrus Fruit

2009 ◽  
Vol 21 (4) ◽  
pp. 533-540 ◽  
Author(s):  
Mitsutaka Kurita ◽  
◽  
Naoshi Kondo ◽  
Hiroshi Shimizu ◽  
Peter Ling ◽  
...  
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Time Lag ◽  
Citrus Fruit ◽  
Ccd Camera ◽  
Fruit Rot ◽  
Fruit Grading ◽  
Image Acquisition System ◽  
Inspection Station ◽  
Uv Leds

There are many types of citrus fruit grading machine with machine vision capability. While most of them sort fruit by size, shape and color, detection of fruit rot remains challenging because their colors are similar with normal parts. Objectives of this research were to investigate if fluorescence would be a good indicator of the fruit rot, and to develop an economical solution to add the rot inspection capability to an existing machine vision fruit inspection station. A machine vision system consisting of a pair of white and UV LED lighting devices and a color CCD camera was proposed for the orange fruit grading task. Since the time lag between the color and fluorescence image captures was short (14 ms), it was possible to inspect color, shape, size, and rot of a fruit on the move before it leaves an existing industrial inspection chamber.

2A1-B07 A Machine Vision System for Citrus Fruit Grading and for Rotten Part Detection

2008 ◽  
Vol 2008 (0) ◽  
pp. _2A1-B07_1-_2A1-B07_4
Author(s):  
Mitsutaka KURITA ◽  
Naoshi KONDO ◽  
Takahisa NISHIZU ◽  
Makoto KURAMOTO ◽  
Yuichi OGAWA ◽  
...  
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Citrus Fruit ◽  
Machine Vision System ◽  
Fruit Grading

Study on the Detection and Selection of Bearing Diameter Based on Machine Vision System

2014 ◽  
Vol 533 ◽  
pp. 298-302
Author(s):  
Fu Sheng Yu ◽  
Sheng Jiang Yin ◽  
Teng Fei Li ◽  
Zhong Guo Sun ◽  
Wei Kang Shi
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Three Dimensional ◽  
Movement Control ◽  
Ccd Camera ◽  
Measuring Method ◽  
Machine Vision System ◽  
Technology Roadmap ◽  
Precision Measuring ◽  
Control Units

A new method and system for inspecting the bearing diameter is developed. The mechanical and movement control units, as well as its machine vision system, are designed. A precision measuring method based on machine vision system is developed to measure bearing diameter. Computer outputs the bearing edge contour and its three-dimensional coordinates after image processing software process the image of bearings which are collected by CCD camera. The controller controls the operation of motor by ball screws and drives the movement of individual parts which can crawls the gripper in the three-dimensional coordinates. Inductive gage is used to measure bearing diameter. Besides, a technology roadmap of image edge character detection is analyzed .Gaussian filter is used to noise reduction of the image and canny operator is used to edge detection. Template match is adapted to the automatic recognition of bearing characteristics. The paper may be helpful to those who work on the same subject in future.

A double image acquisition system with visible and UV LEDs for citrus fruit

2008 ◽  
Author(s):  
Naoshi Kondo ◽  
Takahisa Nishizu ◽  
Yoshihid Minami ◽  
Peter Ling ◽  
Mitsutaka Kurita ◽  
...  
Keyword(s):  
Image Acquisition ◽  
Citrus Fruit ◽  
Acquisition System ◽  
Double Image ◽  
Image Acquisition System ◽  
Uv Leds

Error Optimization of Machine Vision based Tool Movement using a Hybrid CLONALG and PSO Algorithm

2016 ◽  
Vol 7 (1) ◽  
pp. 65-78
Author(s):  
Prasant Kumar Mahapatra ◽  
Anu Garg ◽  
Amod Kumar
Keyword(s):  
Machine Vision ◽  
Hybrid Algorithm ◽  
Vision System ◽  
Ccd Camera ◽  
Pso Algorithm ◽  
Maximum Efficiency ◽  
Machine Vision System ◽  
Tool Positioning ◽  
Tool Position ◽  
Error Optimization

A machine vision system with single monochrome CCD camera and backlight was developed for tool positioning and verification. While evaluating the performance of the developed vision system, the experiments showed that the output of machine vision system was not comparable to the output of sensors embedded in motion stages. Inherent factors like Imaging setup, camera calibration, environmental effects etc. are responsible for the error. These errors must be minimized to achieve maximum efficiency of developed vision system. In this paper, a novel hybrid algorithm is proposed to optimize the tool position error. The proposed algorithm comprises of CLONALG (one of the techniques of Artificial Immune System) and Particle Swarm Optimization (PSO) (a global optimization algorithm). Hybrid algorithm is tested on tool movement ranging from 0.020 mm to 7 mm. Performance of proposed algorithm is evaluated and also compared with CLONALG and PSO algorithms individually.

A Hybrid Algorithm for Optimization of Machine Vision Based Tool Position Error

2014 ◽  
Vol 5 (4) ◽  
pp. 22-33
Author(s):  
Prasant Kumar Mahapatra ◽  
Anu Garg ◽  
Amod Kumar
Keyword(s):  
Machine Vision ◽  
Hybrid Algorithm ◽  
Vision System ◽  
Ccd Camera ◽  
Bat Algorithm ◽  
Position Error ◽  
Tool Positioning ◽  
A Charge ◽  
Tool Position ◽  
Lathe Tool

Tool positioning and its error optimization are gaining considerable importance in engineering applications. A number of machine vision systems have been developed for tool wear and conditioning assessment. A machine vision system for lathe tool position and verification was developed. To evaluate the performance of developed system, images of lathe tool were captured before and after the tool movement with a Charge Coupled Device (CCD) camera. The distance traversed by the tool was calculated from the above images. Difference between the calculated (Image based) and the expected tool movement denotes vision based tool position error. In this paper, a novel hybrid (AIS-Bat) algorithm is proposed to optimize this error in the developed vision system. To prove the effectiveness of proposed algorithm, results were compared with mean technique and bat algorithm, it was observed that proposed algorithm outperforms the other two. Although the results seem promising, still there is a need for better image processing techniques before the application of error optimizing hybrid algorithm.

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

Multifunctional stereoscopic machine vision system with multiple 3D outputs

2020 ◽  
Keyword(s):  
Machine Vision ◽  
International Symposium ◽  
Fast Track ◽  
Vision System ◽  
Machine Vision System ◽  
Stereoscopic Displays ◽  
Electronic Imaging

Fast track article for IS&T International Symposium on Electronic Imaging 2020: Stereoscopic Displays and Applications proceedings.

scholarly journals A real-time machine-vision system for monitoring the textile raising process

2005 ◽  
Vol 56 (8-9) ◽  
pp. 831-842 ◽  
Author(s):  
Monica Carfagni ◽  
Rocco Furferi ◽  
Lapo Governi
Keyword(s):  
Machine Vision ◽  
Real Time ◽  
Vision System ◽  
Machine Vision System ◽  
Time Machine
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