scholarly journals Research on Dimensional Inspection System of Thin Sheet Part Based on Machine Vision

2011 ◽  
Vol 2-3 ◽  
pp. 469-474
Author(s):  
Ji Gang Wu ◽  
Xue Jun Li ◽  
Bin Qin
Keyword(s):  
Machine Vision ◽  
Edge Detection ◽  
Spline Interpolation ◽  
Thin Sheet ◽  
Optimization Method ◽  
Inspection Time ◽  
Inspection System ◽  
Adaptive Optimization ◽  
Dimensional Inspection ◽  
Vision Inspection

Key technologies of dimensional inspection system of thin sheet part based on machine vision are investigated, and an entire machine vision inspection system is developed. A cad information-based line scanning step adaptive optimization method used for image grabbing of inspected part is proposed. A rectangle lens subpixel edge detection method based on cubic spline interpolation used for edge detection is advanced. A planar contour primitive recognition method based on curvature and HOUGH transform used for image recognition is raised. The inspection accuracy of the inspection system can reach to 1μm, and the inspection time can satisfy the requirements of on-line real-time inspection, so the inspection system is feasible.

Research on Edge Detection of Thin Sheet Part Dimension Inspection System Based on Machine Vision

2011 ◽  
Vol 103 ◽  
pp. 194-198
Author(s):  
Ji Gang Wu ◽  
Kuan Fang He ◽  
Bin Qin
Keyword(s):  
Machine Vision ◽  
Edge Detection ◽  
Mathematical Morphology ◽  
Detection Method ◽  
Thin Sheet ◽  
Laplacian Operator ◽  
Inspection System ◽  
Edge Location ◽  
Edge Detection Method ◽  
Part Dimension

Aiming at the edge detection of thin sheet part dimension inspection system based on machine vision, a contrast research on edge detection is investigated. The Gaussian blurred simulation image and thin sheet part image are took as evaluation images, and the edge detection are done with Roberts operator, Sobel operator, Prewitt operator, Kirsch operator, Laplacian operator, LOG operator and mathematical morphology edge detection method. The results of edge detection are analyzed deeply, and the edge location accuracy, noise resisting ability and calculation time of each algorithm are compared. The single-pixel width connected contour is acquired with mathematical morphology edge detection method, the detection time are 0.0521 second and 0.457 second respectively. It is appropriate that taking the mathematical morphology edge detection method as the edge detection method of thin sheet part dimension inspection system based on machine vision.

Intelligent Vision Inspection System for IC Engine Head: An ANN Approach

2012 ◽  
Vol 479-481 ◽  
pp. 2242-2245 ◽  
Author(s):  
Rajesh Kanna ◽  
Manikandan Saravana
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Back Propagation ◽  
Engine Block ◽  
Inspection System ◽  
Back Propagation Algorithm ◽  
Ic Engine ◽  
Vision Inspection ◽  
System Module ◽  
Artificial Neural Network Ann

A machine vision system based on Artificial Neural Network (ANN) for inspection of IC Engine block was developed to identify the misalignment and improper diminishing of holes in the IC Engine block. The developed machine vision and ANN module is compared with the commercial MATLAB® software and found results were satisfactory. This work is broadly divided into four stages, namely Intelligent inspection module, Machine Vision module, ANN module and Expert system module. A system with a camera was used to capture the various segments of head of the IC Engine block. The captured bitmap format image of IC Engine block has to be filtered to remove the noises present while capturing and the size is also altered using SPIHT method to an acceptable size and will be given as input to ANN. Generalized ANN with Back-propagation algorithm was used to inspect the IC Engine block. ANN has to be trained to provide the inspected report.

Research on Inspection System Formation of Cells in Gravure Cylinder Base on Machine Vision

2010 ◽  
Vol 174 ◽  
pp. 207-210
Author(s):  
Zi Fen He ◽  
Zhao Lin Zhan ◽  
Yin Hui Zhang
Keyword(s):  
Machine Vision ◽  
Production Management ◽  
Process Analysis ◽  
Image Sensor ◽  
Inspection System ◽  
Canny Operator ◽  
Vision Inspection ◽  
Sobel Operator ◽  
Dark Tone ◽  
Machine Vision Inspection

This paper presents a machine vision inspection system to detect deformation of cells in the process of gravure manufacturing, which can provide real-time reporting and detail testing process analysis and find problems and make adjustments to track the production process, more conducive to scientific production management. The formation of cells of gravure machine vision inspection system is able to change analog signal into digital signal of gravure image. We have applied the MATLAB image processing software to read the experiment images and histogram equalization. The edge of cells is extracted by using of Sobel operator and Canny operator. We use different thresholds and experimental sigma values that compare to experimental results. It is found that extraction using the Canny operator is better than Sobel operator. Canny edge extraction operator is best when the value of sigma is 16. According to the image used in this research to determine the standard cells carving the value of gaps d0 equals 125, the value of dark tone s0 equals 394, so its standard value of gaps and dark tone are d0 ± 10 and s0 ± 10. The value of gravure outlets gaps and dark tone are measured, while d and s is in the scope of standard range, which the output 1 of the cells determined to pass and the output 0 deemed to fail. We propose two solutions of cells deformation gravure machine vision inspection system. Through analysis and comparison of performance and economic of the lighting and image sensor, the final implementation of the program is identified.

scholarly journals Measurements of surface flatness distortions using machine vision inspection system

Mechanik ◽  
2017 ◽  
Vol 90 (12) ◽  
pp. 1155-1156
Author(s):  
Anna Zawada-Tomkiewicz ◽  
Dariusz Tomkiewicz ◽  
Lesław Wilk
Keyword(s):  
Thermal Treatment ◽  
Machine Vision ◽  
Vision System ◽  
Float Glass ◽  
Inspection System ◽  
Vision Inspection ◽  
Surface Flatness ◽  
Machine Vision Inspection

The use of a vision system for evaluating the flatness distortion of float glass under thermal treatment in a horizontal process is presented. The possibility of evaluation of such parameters as overall bow, roller wave and edge lift was analyzed for a pane of glass taken from production.

scholarly journals Planar Contour Primitive Recognition of Thin Sheet Part Dimensional Inspection System

2011 ◽  
Vol 2-3 ◽  
pp. 463-468
Author(s):  
Ji Gang Wu ◽  
Kuan Fang He ◽  
Bin Qin
Keyword(s):  
Hough Transform ◽  
Thin Sheet ◽  
Detection Methods ◽  
Inspection System ◽  
Threshold Method ◽  
Dimensional Inspection ◽  
Straight Line ◽  
Dominant Point ◽  
Contour Point ◽  
Point Detection

According to the two indices of inspection accuracy and inspection speed, a planar contour primitive recognition method of thin sheet part dimensional inspection system based on curvature and HOUGH transform is proposed. A contour point classification algorithm based on neighborhood values is developed, and a curvature threshold method is selected to filter the contour points, and a projection height method is selected to distinguish the property of the primitive and classify the contour points, and the straight line primitive and arc primitive segmentation and merging algorithms are constructed respectively by HOUGH transform. The inspection accuracy and inspection speed of the proposed method are compared and analyzed by contrast experiments between the proposed method and four dominant point detection methods such as Chung & Tsai method and so on. The dominant point detection ability of the proposed method is tested by a simulation planar contour which includes all kinds of dominant points. The experimental results indicate that the proposed method can recognize primitives exactly, the inspection speed is fast and the universality is good.

Machine Vision Inspection of In Vitro Diagnostic Kits

2013 ◽  
Vol 753-755 ◽  
pp. 2164-2169
Author(s):  
Jiang Ping Mei ◽  
Yi Liu
Keyword(s):  
Machine Vision ◽  
Surface Defects ◽  
Detection Threshold ◽  
Inspection System ◽  
Strip Surface ◽  
Diagnostic Kits ◽  
Vision Inspection ◽  
In Vitro Diagnostic ◽  
Machine Vision Inspection

A machine vision-based inspection system was proposed to inspect the defects of in-vitro diagnostic kits in the production line. The proposed system consisted of two sub-systems, which inspect the strip surface defects and strip assembly defects respectively. The procedure to inspect five types of major defects was determined by the application of image processing and analysis techniques such as image enhancement, edge detection, threshold segmentation, and morphology. The proposed system was implemented using 300 defect samples. Experimental results show the proposed system is effective and efficient.

Sign in / Sign up

Export Citation Format

Share Document