scholarly journals Defect Detection Techniques for Airbag Production Sewing Stages

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Raluca Brad ◽  
Lavinia Barac ◽  
Remus Brad
Keyword(s):  
Image Processing ◽  
Quality Control ◽  
Defect Detection ◽  
Automatic Detection ◽  
Color Pattern ◽  
Processing Methods ◽  
Detection Techniques ◽  
Sewing Thread ◽  
Detection Of Defects

Airbags are subjected to strict quality control in order to ensure passengers safety. The quality of fabric and sewing thread influences the final product and therefore, sewing defects must be early and accurately detected, in order to remove the item from production. Airbag seams assembly can take various forms, using linear and circle primitives, with threads of different colors and length densities, creating lockstitch or double threads chainstitch. The paper presents a framework for the automatic detection of defects occurring during the airbag sewing stage. Types of defects as skipped stitch, missed stitch, or superimposed seam for lockstitch and two threads chainstitch are detected and marked. Using image processing methods, the proposed framework follows the seams path and determines if a color pattern of the considered stitches is valid.

Evaluation of Computer-assisted Image Enhancement in Minimal Invasive Endoscopic Surgery

2004 ◽  
Vol 43 (04) ◽  
pp. 362-366 ◽  
Author(s):  
F. Vogt ◽  
W. Hohenberger ◽  
D. Paulus ◽  
H. Niemann ◽  
C. H. Schick ◽  
...  
Keyword(s):  
Image Processing ◽  
Minimal Invasive ◽  
Image Sequences ◽  
Computer Assisted ◽  
Processing Methods ◽  
Temporal Filtering ◽  
Endoscopic Images ◽  
Filter Size ◽  
Image Pairs

Summary Objectives: This paper focusses on the evaluation of the usage of computer-aided image processing methods for minimal invasive surgery. During video endoscopy of visceral cavities the images are displayed directly on the monitor without further processing. In the course of the operation the former good quality of the images decreases due to typical disturbances like bleeding, smoke or flying particles. These disturbances can be reduced by using image processing methods like color normalization, temporal filtering or equalization. Methods: In this double-blinded analysis, 14 surgeons with different levels of experience evaluated 120 image pairs and 5 image sequences, directly comparing original and processed images or movies. Results: Color normalization and equalization proved to significantly enhance video endoscopic images. With regard to temporal filtering, an improvement could be seen in the image sequences with filter size 5 being a greater enhancement than filter size 3. Comparing the state of experience and its influence on the results, it occurred that the experienced surgeons preferred the original color while altogether agreeing that the color-normalized images were better. Conclusions: The results obtained in the present evaluation show that the image processing methods which were used can significantly improve the quality of video endoscopic images. As a result of this, necessary lavages of the operated area are reduced and a better overview and orientation for the surgeon can be reached.

INTEGRATED APPROACH FOR DEFECT DETECTION IN CERAMIC TILES

2012 ◽  
Vol 3 (2) ◽  
pp. 259-262 ◽  
Author(s):  
Meenakshi Sharma ◽  
Gurleen Kaur
Keyword(s):  
Quality Control ◽  
Defect Detection ◽  
Ceramic Tile ◽  
Texture Features ◽  
Integrated Approach ◽  
Experimental Results ◽  
Ceramic Tiles ◽  
Classification Technique ◽  
Color Features

Quality control is an important issue in the ceramic tile industry. Price of ceramic tiles also depends on purity of texture, accuracy of color, shape etc. Considering this criteria, an integrated  defect detection and classification technique has been proposed which plays an important role in ceramic tiles industries to detect the defects and to control the quality of ceramic tiles.GLCM extracts the  texture features and these features  together with color features are used for analysis in classifiers such as SVM, KNN and Bayesian. Experimental results illustrated that  every classifier gives highest accuracy with HSV.

scholarly journals Android-based automatic detection and measurement system of highway billboard for tax calculation in indonesia

2019 ◽  
Vol 14 (2) ◽  
pp. 877 ◽  
Author(s):  
Romi Fadillah Rahmat ◽  
Sarah Purnamawati ◽  
Handra Saito ◽  
Muhammad Fariz Ichwan ◽  
Tri Murti Lubis
Keyword(s):  
Image Processing ◽  
Measurement System ◽  
Image Acquisition ◽  
Automatic Detection ◽  
Measurement Process ◽  
Distance Method ◽  
Processing Methods ◽  
Distance Calculation ◽  
The Government ◽  
Point Distance

<span>Billboards are objects, tools or actions, which based on the characteristics serve its own purpose to earn profits, advertise certain people or service, and to draw public’s attention by placing it in a very strategic place. It has led the government to charge tax on billboards based on its location, dimensions, and viewpoints. Therefore, authorized parties have to be able to ensure the data authenticity of the proposed billboards. One of the obstacles in data verification is the time of billboards measurement process due to its size and height from the ground, based on this problem, and we developed a system which can measure the dimensions of billboards without physically touching it by implementing image processing methods to identify the billboards. The implementation is by measuring the dimensions of the billboards using perspective concept, then calculates the distance between the camera and the object using two-point distance calculation GPS coordinates. The results showed that the distance calculation using the GPS method generated inaccurate values, whereas the systematic distance method generated a result of errors’ range from 0.5 to 25 cm if the image acquisition is performed nearly perpendicular to the object.</span>

scholarly journals An Industrial Vision System to Analyze the Wear of Cutting Tools

2017 ◽  
Vol 869 ◽  
pp. 183-194
Author(s):  
Christina Gillmann ◽  
Tobias Post ◽  
Benjamin Kirsch ◽  
Thomas Wischgoll ◽  
Jörg Hartig ◽  
...  
Keyword(s):  
Image Processing ◽  
Cutting Tool ◽  
Wear Behavior ◽  
Vision System ◽  
Cutting Tools ◽  
Processing Methods ◽  
Comparative Visualization ◽  
Image Series ◽  
Measurement And Evaluation

The wear behavior of cutting tools directly affects the quality of the machined part. The measurement and evaluation of wear is a time consuming and process and is subjective. Therefore, an image-based wear measure that can be computed automatically based on given image series of cutting tools and an objective way to review the resulting wear is presented in this paper. The presented method follows the industrial vision system pipeline where images of cutting tools are used as input which are then transformed through suitable image processing methods to prepare them for the computation of a novel image based wear measure. For multiple cutting tool settings a comparative visualization of the wear measure outputs is presented. The effectiveness of the presented approach is shown by applying the method to measure the wear of four different cutting tool shapes.

scholarly journals Terrestrial Method for Airborne Lidar Quality Control and Assessment

2014 ◽  
Vol XL-1 ◽  
pp. 45-49 ◽  
Author(s):  
N. M. Alsubaie ◽  
H. M. Badawy ◽  
M. M. Elhabiby ◽  
N. El-Sheimy
Keyword(s):  
Quality Control ◽  
Edge Detection ◽  
Laser Scanning ◽  
A Priori ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Data Quality Control ◽  
Detection Techniques

Most of LiDAR systems do not provide the end user with the calibration and acquisition procedures that can use to validate the quality of the data acquired by the airborne system. Therefore, this system needs data Quality Control (QC) and assessment procedures to verify the accuracy of the laser footprints and mainly at building edges. This research paper introduces an efficient method for validating the quality of the airborne LiDAR point clouds data using terrestrial laser scanning data integrated with edge detection techniques. This method will be based on detecting the edge of buildings from these two independent systems. Hence, the building edges are extracted from the airborne data using an algorithm that is based on the standard deviation of neighbour point's height from certain threshold with respect to centre points using radius threshold. The algorithm is adaptive to different point densities. The approach is combined with another innovative edge detection technique from terrestrial laser scanning point clouds that is based on the height and point density constraints. Finally, statistical analysis and assessment will be applied to compare these two systems in term of edge detection extraction precision, which will be a priori step for 3D city modelling generated from heterogeneous LiDAR systems

scholarly journals A Research on Fruit Maturity Detection Techniques

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1470-1473
Keyword(s):  
Image Processing ◽  
Permissible Limit ◽  
Human Consumption ◽  
Processing Methods ◽  
Detection Techniques ◽  
Fruit Maturity ◽  
Different Types

Fruits are the major source of food to humans. Damage in fruits can be of different types. Damage due to insects or damage during transportation are the most common types of damages caused. Fruits are also unfit for human consumption when they mature beyond permissible limit which can be termed as rotten. Fruit maturity detection is divided into different stages depending on type of fruit detection used. Various sensors and image processing methods are used for this purpose. The major stages involved in this process are pre-processing, detection using sensors and image processing. Spectroscopy has been a huge development in image processing. In later stages the results are classified or clustered according to the requirement. This paper presents a survey of the existing fruit maturity detection techniques.

scholarly journals A Brief Review and Advances of Thermographic Image - Processing Methods for IRT Inspection: a Case of Study on GFRP Plate

2020 ◽  
Author(s):  
F.W. Panella ◽  
A. Pirinu ◽  
V. Dattoma
Keyword(s):  
Image Processing ◽  
Data Processing ◽  
Defect Detection ◽  
Ratio Method ◽  
Computation Method ◽  
Internal Damage ◽  
Processing Methods ◽  
Mapping Procedure ◽  
Local Boundary ◽  
Thermal Data

AbstractThe present work introduces a different data processing strategy, proposed in order to improve sub-surface defect detection on industrial composites; in addition, a resume of thermal data processing with most common algorithms in literature is presented and applied with new data. A deep comparison between the common absolute contrast, DAC, PCT, TSR and derivative methods and a new proposed contrast mapping procedure is implemented. Thermographic inspection was done in reflection mode on a Glass Fiber Reinforced Plastic plate, with flat bottom hole defects. Thermal data computation method is found to be critical for simultaneous defect detection and automatic mapping, optimized to identify defect boundaries at specific depth, with help of accurate image processing, implemented in a Matlab GUI for a reliable and rapid characterization of internal damage. The new processing approach, the Local Boundary Contrast method, elaborates different contrast maps and facilitates recognition of damage extension. Tanimoto criterion and the signal-to-noise ratio method were applied as a criterion to assess defect detectability of various processing methods.

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