Automatic Inspection System for Grain Size Distribution Using a Commercial Grind Gauge

2008 ◽  
Vol 381-382 ◽  
pp. 323-324
Author(s):  
M. Yoshida ◽  
Kazuhisa Yanagi ◽  
M.H. Hafiz ◽  
M. Hara
Keyword(s):  
Image Processing ◽  
Image Data ◽  
Ccd Camera ◽  
Inspection System ◽  
Automatic Inspection ◽  
Image Processing Algorithm ◽  
Measurement Results ◽  
Optical Configuration ◽  
Processing Techniques ◽  
Measuring Tool

Grind gauge is a measuring tool for size of grains or particles included in paint or ink. Its geometrical specifications and operational procedure are regulated to some extent and partly standardized in both ISO and JIS. However, only skilled technician can manage to handle it properly and to obtain correct measurement results. The objective of this study is to develop an automatic inspection system for the grain or particle size by use of artificial lighting and CCD camera with image processing techniques. A telecentric lens system was constructed and high resolution CCD camera was attached to it. Advantages of coaxial illumination and oblique illumination methods were revealed and their applicability was examined respectively. The optical configuration to cover the scale and the whole groove width of grind gauge was devised so that the captured image data could contain both grain/particle distribution and height location. A proper software program followed by image processing algorithm was established to reveal particle mark and liner mark.

scholarly journals Smart Dye Inspection System in Textile Industry

2020 ◽  
Vol 8 (6) ◽  
pp. 5061-5063
Keyword(s):  
Image Processing ◽  
Reference Material ◽  
Textile Industry ◽  
High Accuracy ◽  
Inspection System ◽  
Manual Operation ◽  
Image Processing Techniques ◽  
Manual Inspection ◽  
Processing Techniques

Inspection on the dyed material in the textile industry is facing a challenging task owing to the accurate measurement of the dye concentration added. Currently manual inspection is done. It consumes more time and less accurate. The proposed work provides a solution to above problem. The image of reference material (cloth) is captured and the features are extracted using image processing techniques. The color concentration of both the reference material and the test fabric is compared. If the dye concentration of the test fabric matches with the reference material, then it is a perfect dyed cloth whereas for mismatched samples, the concentration is to be adjusted is displayed. This smart dyeing inspection system reduces the manual operation and saves time and results in high accuracy.

The External Thread Detection of Liquefied Gas Valve Based on Image Processing Technology

2013 ◽  
Vol 658 ◽  
pp. 551-554
Author(s):  
Xiao Dong Wang ◽  
Bo Liu ◽  
Xiao Wei Chen ◽  
Wei Zhang ◽  
Zhi Gang Guo
Keyword(s):  
Image Processing ◽  
Detection Efficiency ◽  
Ccd Camera ◽  
Contact Detection ◽  
Standard Size ◽  
External Thread ◽  
Thread Profile ◽  
Processing Techniques ◽  
Liquefied Gas

For liquefied gas valve external thread detections, the gauges traditional external thread detection. Although this method simply, easy to operate, but the detection process in contact with the thread and thus cannot guarantee the quality of the thread and the low detection efficiency. The external thread detection of liquefied gas valve based on image processing techniques adopts a non-contact detection. CCD camera collects image of the external thread and transmitted to the computer by the acquisition board. Thus image preprocessing, image segmentation and then get the thread edge contour. Finally, Matched thread profile .By comparing with the standard size tape to determine eligibility. The experimental results show that this method is feasible.

Research on the High-Speed Object Shadowgraph Image Processing Method Based on Adaptive Threshold Segmentation

2013 ◽  
Vol 325-326 ◽  
pp. 1571-1575
Author(s):  
Fang Wang ◽  
Zong Wei Yang ◽  
De Ren Kong ◽  
Yun Fei Jia
Keyword(s):  
Image Processing ◽  
High Speed ◽  
Center Of Mass ◽  
Image Data ◽  
Ccd Camera ◽  
Adaptive Threshold ◽  
Processing Method ◽  
Laser Source ◽  
Feature Points ◽  
Threshold Segmentation

Shadowgraph is an important method to obtain the flight characteristics of high-speed object, such as attitude and speed etc. To get the contour information of objects and coordinates of feature points from shadowgraph are the precondition of characteristics analysis. Current digital shadowgraph system composed of CCD camera and pulsed laser source is widely used, but still lack of the corresponding method in image processing. Therefore, the selection of an effective processing method in order to ensure high effectiveness and accuracy of image data interpretation is an urgent need to be solved. According to the features of shadowgraph, a processing method to realize the contour extraction of high-speed object by adaptive threshold segmentation is proposed based on median filtering in this paper, and verified with the OpenCV in VC environment, the identification process of the feature points are recognized. The result indicates that by using this method, contours of high-speed objects can be detected nicely, to combine relevant algorithm, the pixel coordinates of feature points such as the center of mass can be recognized accurately.

AIRCRAFT CLASSIFICATION USING IMAGE PROCESSING TECHNIQUES AND ARTIFICIAL NEURAL NETWORKS

2011 ◽  
Vol 25 (08) ◽  
pp. 1321-1335 ◽  
Author(s):  
ADIL GURSEL KARACOR ◽  
ERDAL TORUN ◽  
RASIT ABAY
Keyword(s):  
Image Processing ◽  
Image Data ◽  
Radar Data ◽  
Still Image ◽  
Image Processing Techniques ◽  
Black And White ◽  
Rf Signals ◽  
Different Types ◽  
Artificial Neural ◽  
Processing Techniques

Identifying the type of an approaching aircraft, should it be a helicopter, a fighter jet or a passenger plane, is an important task in both military and civilian practices. The task in question is normally done by using radar or RF signals. In this study, we suggest an alternative method that introduces the use of a still image instead of RF or radar data. The image was transformed to a binary black and white image, using a Matlab script which utilizes Image Processing Toolbox commands of Matlab, in order to extract the necessary features. The extracted image data of four different types of aircraft was fed into a three-layered feed forward artificial neural network for classification. Satisfactory results were achieved as the rate of successful classification turned out to be 97% on average.

scholarly journals Automated Bird Species Recognition System Based on Image Processing and Svm Classifier

2021 ◽  
Vol 12 (2) ◽  
pp. 351-356
Author(s):  
Chandra. B, Et. al.
Keyword(s):  
Image Processing ◽  
Species Recognition ◽  
Bird Species ◽  
Image Data ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Svm Classifier ◽  
Data Set ◽  
Learning Techniques ◽  
Processing Techniques

Here, in this study we can learn about Bird species recognition. In forest areas cameras are fixed at various locations which capture images periodically. From those images the birds living in such dense forest areas can be identified. It would be useful if we can able to classify the species of birds with the help of those images. But that is not an easy task because of the variations in the light effects, illumination and camera viewpoints. So we need to involve image processing techniques for preprocessing the captured image and also deep learning techniques are to be implemented for classifying the images. For classification purpose training is to be done with the help of image data set. Here we propose a method of discriminating birds by means of the ratio of the distance between eye and beak to that of the beak width. By combining this mythology with image processing and SVM classification technique a new bird species recognition algorithm is proposed. The proposed new methodology will improve the accuracy in classifying.

Case Studies of the Use of Image Processing in Metrology and Failure Analysis

2005 ◽  
Author(s):  
Kartik Ramanujachar
Keyword(s):  
Image Processing ◽  
Failure Analysis ◽  
Case Studies ◽  
Nearest Neighbor ◽  
Image Data ◽  
Cumulative Distribution ◽  
Information Theoretic ◽  
Atomic Force ◽  
Processing Techniques

Abstract This paper describes the use of image processing techniques in metrology and failure analysis with the help of three case studies. The first study concerns a technique that significantly automates the process and hence enables both a rapid and accurate extraction of cumulative distribution function for transistor CD through the use of edge detection and quantification of image intensities. The second study is about utilizing a cross correlation algorithm and an appropriately chosen sample and image to estimate the "on image" spatial resolution of an scanning electron microscope. The last case study uses image data acquired with an atomic force microscope. The paper describes how information theoretic concepts like entropy and mutual information combined with image segmentation and nearest neighbor extraction can be used to isolate those regions of the AFM scan that can potentially benefit from further analysis.

A Study on Various Image Processing Techniques and Hardware Implementation Using Xilinx System Generator

2017 ◽  
pp. 215-230
Author(s):  
Jyotsna Rani ◽  
Ram Kumar ◽  
Abahan Sarkar ◽  
Fazal A. Talukdar
Keyword(s):  
Image Processing ◽  
Hardware Implementation ◽  
Image Data ◽  
Tool Support ◽  
Environment Design ◽  
Image Processing Techniques ◽  
System Generator ◽  
Xilinx System Generator ◽  
Support Software ◽  
Processing Techniques

This article reviews the various image processing techniques in MATLAB and also hardware implementation in FPGA using Xilinx system generator. Image processing can be termed as processing of images using mathematical operations by using various forms of signal processing techniques. The main aim of image processing is to extract important features from an image data and process it in a desired manner and to visually enhance or to statistically evaluate the desired aspect of the image. This article provides an insight into the various approaches of Digital Image processing techniques in Matlab. This article also provides an introduction to FPGA and also a step by step tutorial in handling Xilinx System Generator. The Xilinx System Generator tool is a new application in image processing and offers a friendly environment design for the processing. This tool support software simulation, but the most important is that can synthesize in FPGAs hardware, with the parallelism, robust and speed, this features are essentials in image processing. Implementation of these algorithms on a FPGA is having advantage of using large memory and embedded multipliers. Advances in FPGA technology with the development of sophisticated and efficient tools for modelling, simulation and synthesis have made FPGA a highly useful platform.

scholarly journals Image Processing for Sustainable Remodeling: Introduction to Real-time Quality Inspection System of External Wall Insulation Works

2019 ◽  
Vol 11 (4) ◽  
pp. 1081 ◽  
Author(s):  
Sang-Ho Cho ◽  
Kyung-Tae Lee ◽  
Se-Heon Kim ◽  
Ju-Hyung Kim
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Image Data ◽  
Inspection System ◽  
Quality Inspection ◽  
Labor Costs ◽  
External Wall ◽  
Graphic Data ◽  
Repair Costs ◽  
Serious Injury

The external wall insulation method was introduced to enhance the energy efficiency of existing buildings. It does not cause a decrease of inner space and costs less in comparison to methods that insert insulation panels inside walls. However, it has been reported that external wall insulation boards are disconnecting from walls due to malfunctions of the adhesive. This causes not only repair costs, but also serious injury to pedestrians. Separation problems occur when the bonded positions are incorrect and/or the total area and thickness of the adhesive is smaller than the required amount. A challenge is that these faults can hardly be inspected after installing boards. For this reason, a real-time inspection system is necessary to detect potential failure during adhesive works. Position, area and thickness are major aspects to inspect, and thus a method to process image data of these seems efficient. This paper presents a real-time quality inspection system introducing image processing technology to detect potential errors during adhesive works of external wall insulation, and it is predicted to contribute to achieving sustainable remodeling construction by reducing squandered material and labor costs. The system consists of a graphic data creation module to capture the results of adhesive works and a quality inspection module to judge the pass or fail of works according to an algorithm. A prototype is developed and validated against 100 panels with 800 adhesive points.

Research and Application of Coordination Controller in Web Inspection System (WIS)

2012 ◽  
Vol 562-564 ◽  
pp. 1832-1835
Author(s):  
Xing Guang Qi ◽  
Cai Sheng Shen
Keyword(s):  
Image Processing ◽  
Modular Design ◽  
Processing System ◽  
Ccd Camera ◽  
Working Environment ◽  
Inspection System ◽  
Fpga Design ◽  
Coordinate Control ◽  
Web Inspection ◽  
Image Management System

The study and application of the coordination controller in Web Inspection System (WIS) involves the field of industrial inspection and machine vision technology. The online WIS consists of roller equipment, coordination controller, switch controller, a number of cameras, image management system and management server. Coordination controller based on FPGA design and the LVDS interface, CAN bus interface, is connected through the line with roller equipment, switch controller and a number of camera management server. The CCD camera is connected through the line with image processing systems, and the image processing system connected with management server. Coordinated controller uses a modular design to coordinate control system operation, reduce the CPU load and improve the efficiency of paper defect detection. It is also highly integrated, and able to reduce cabling and costs, so as to raise the efficiency of the controller development, reduce staff workload and improve the working environment.

Size and Defect Detection of Hami Big Jujubes Based on Computer Vision

2012 ◽  
Vol 562-564 ◽  
pp. 750-754 ◽  
Author(s):  
Ben Xue Ma ◽  
Xiang Xiang Qi ◽  
Li Li Wang ◽  
Rong Guang Zhu ◽  
Qin Gang Chen ◽  
...  
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Image Data ◽  
Ccd Camera ◽  
Transverse Diameter ◽  
Testing Time ◽  
Hardware System ◽  
Space Transformation ◽  
Visual Basic6.0 ◽  
Mean And Variance

In order to realize the rapid nondestructive testing for Hami Big Jujubes’ quality detection, a detecting system based on computer vision was established to detect Hami Big Jujubes’ size and defect. The image grabbing card and CCD camera were consisted of the hardware system, which was used to collect image data. Visual Basic6.0 and image processing toolbox of Mil9.0 constituted the software system. The function of MIL9.0 was called in the Visual Basic6.0 to realize the detection. During image processing, the threshold was all chose (0.1,0.7).Many methods were used to identify the features rapidly and get the H value’s mean and variance, such as colour space transformation, mathematical morphology processing and mask etc. Experimental results showed that the correlation coefficient between the projective areas and weights was 0.945.The correlation between projective areas, transverse diameter and vertical diameter was 0.951.The defects grading models were built by BP neural network .The discriminating rate was as high as 99.16％ in training set，and 91.43％ in prediction set. The average testing time was 80 milliseconds, which can satisfy the detection system’s requirements of time．

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