An Integrated System For Quality Inspection Of Tiles (original) (raw)
Related papers
2005
One of many applications of vision systems is quality control. Quality control in ceramic tile manufacturing is hard, labor-intensive operation. Ceramic tiles classification depends on three main factors color analysis, dimension verification, and surface defects. Our work introduces enhanced algorithms to detect the color and surface defects in the fired ceramic tiles using principles of image processing analysis. This algorithm assumed as a visual inspection system that helps in the sorting operation before packing operation to improve the homogeneity of batches received by costumer.
Intelligent Machine Vision System for Automated Quality Control in Ceramic Tiles Industry
2010
Intelligent system for automated visual quality control of ceramic tiles based on machine vision is presented in this paper. The ceramic tiles production process is almost fully and well automated in almost all production stages with exception of quality control stage at the end. The ceramic tiles quality is checked by using visual quality control principles where main goal is to successfully replace man as part of production chain with an automated machine vision system to increase production yield and decrease the production costs. The quality of ceramic tiles depends on dimensions and surface features. Presented automated machine vision system analyzes those geometric and surface features and decides about tile quality by utilizing neural network classifier. Refined methods for geometric and surface features extraction are presented also. The efficiency of processing algorithms and the usage of neural networks classifier as a substitution for human visual quality control are conf...
Advanced Grading System for Quality Assurance of Ceramic Tiles based using Digital Image Processing
Abstract Objectives: To design an automated advanced grading system for maintaining quality assurance of ceramic tiles. Methods/ Statistical Analysis: We designed a machine that name is Upgraded Automated High Quality Maintaining Machine (UAHQMM). Customers required effect less and quality ceramic tiles. Findings: The block diagram of this research work presented three phases for automated quality Maintaining machine to maintain quality in ceramic tile industry. Application/Improvements: This automated machine is very useful for corner defect detection from different shapes of ceramic tile. In this research we discussed two shapes square and rectangle shapes. This modeled machine is very helpful for increasing production rate.
Ceramic Tile Border Defect Detection Algorithms in Automated Visual Inspection System
Journal of American …, 2011
Automated Visual Inspection Systems (AVIS) are becoming increasingly popular due to low cost maintenance and high accuracy. Ceramic tile factories, for example, are very much interested in these sorts of systems. This paper introduces a different strategy in ceramic tile inspection system to reveal four major problems, namely, edge curvature, thickness, size measuring and edge crack defects. It is believed that this method will cover edge curvature defects and thickness measuring of ceramic tiles in AVIS with recommending an individual algorithm for each defect based on line feature extraction techniques. In addition, it is assumed that our model makes size measuring and edge defects detection easier and more accurate rather than previous approaches. This proposed model will allow ceramic tile companies to perform quality control inspection without costly measuring tools or error-prone inspection by humans. Moreover, factories have to install and apply Flatness Control Machine (FCM) to measure the flatness curvature of ceramic tiles. This machine keeps the ceramic tiles in fixed position to investigate the upper surface only. But our strategy is independent of a specific position through inspection in various angles from top and side views. We hope that our model, which is prominent in low cost implementation, will enable companies to apply this method in different situations in their manufacturing production line systems. Hence, it will assist them to produce not only more accurate reports on defects but also permit improved manufacturing of quality products.
Surface defects detection for ceramic tiles using image processing and morphological techniques
world academy of science, engg and …, 2005
Abstract⎯ Quality control in ceramic tile manufacturing is hard, labor intensive and it is performed in a harsh industrial environment with noise, extreme temperature and humidity. It can be divided into color analysis, dimension verification, and surface defect detection, which is the main purpose of our work. Defects detection is still based on the judgment of human operators while most of the other manufacturing activities are automated so, our work is a quality control enhancement by integrating a visual control stage using image processing and morphological operation techniques before the packing operation to improve the homogeneity of batches received by final users.
Ceramic Tiles Quality Inspection Using Statistical Methods and Neural Networks Approach
2015
The image processing described in this paper is used for visual quality inspection in ceramic tile production. The tiles surface quality depends on the surface defects and has the influence to the tile quality classification. The described image processing is based on the neural network approach. The described diagnostic algorithm is presented to detect surface failures on white ceramic tiles. The tiles are scanned and the digital images are pre-processed and classified using neural networks. Pre-processing of the image data is used to keep the number of inputs of the neural networks performing the classification relatively small. It is important to reduce the amount of input data with problem specific pre-processing. Statistical methods are used in the pre-proccesing of the image data. For classification purposes, a probabilistic neural network and a standard feedfoward neural network are used and the results obtained are compared. The analysis of the detection capabilities is done...
Integrated Approach for Defect Detection in Ceramic Tiles
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2012
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.
Automatic color grading of ceramic tiles using machine vision
IEEE Transactions on Industrial Electronics, 1997
We present a method designed to solve the problem of automatic color grading for industrial inspection of plain and patterned ceramic tiles. We discuss problems we were confronted with, like the temporal and spatial variation of the illumination, and the ways we dealt with them. Then, we present results of correctly grading a series of ceramic tiles, the differences of which were at the threshold of human perception.
Automated Quality Inspection on Tile Border Detection using Vision System
International Journal of Recent Technology and Engineering (IJRTE), 2019
Most of the ceramic tile industry still doing the quality control by manually. The accuracy of the manual inspection by human is lower due to the harsh industrial environment with noise, extreme temperature and humidity. A camera should replace the human eyes to recognise the defect tile effectively. Thus, a suitable method have to investigate for implementing this function. This project aim to design and develop an automated quality inspection in ceramic tile industry using vision system. The performance of the system is analysed. An Imaging Source CMOS industrial camera is use to capture the tile border. Image processing with edge detection technique is use to analyse the captured image of tile border and identify the defective tiles. The image filtering and intensity of the light are adjust to evaluate the performance of the system. The overall automation process involves image capturing, image processing, and decision making. The defect detection algorithms are develop to differ...
Automated Control of Surface Defects on Ceramic Tiles Using 3D Image Analysis
Materials
This paper presents a method of acquisition and analysis of three-dimensional images in the task of automatic location and evaluation of defects on the surface of ceramic tiles. It presents a brief description of selected defects appearing on the surface of tiles, along with the analysis of their formation. The paper includes the presentation of the method of constructing a 3D image of the tile surface using the Laser Triangulation Method (LTM), along with the surface imaging parameters employed in the research. The algorithms of three-dimensional surface image analysis of ceramic tiles used in the process of image filtering and defect identification are presented. For selected defects, the method of measuring defect parameters and the method of visualization of defects on the surface are also presented. The developed method was tested on defective products to confirm its effectiveness in the field of quick defect detection in automated control systems installed on production lines.