Series in Machine Perception and Artificial Intelligence, 2000

Despite the obvious needs of applications, texture analysis is a rare method in automated visual inspection outside textile industry. Most textures in the real world are non-uniform, the inspection speed requirements extreme and very difficult to satisfy at a reasonable cost using textbook methods. Furthermore, the costs of retraining the systems tend to exceed any acceptable level. This paper gives a brief overview of the problem space of applying texture analysis for industrial inspection, presenting some solutions proposed and their prerequisites.

1988

In this paper, we will review some visual inspection problems that were presented to our laboratory by a con- sortium of Belgian industrial companies. These problems were selected to serve as a test vehicle for a software pack- age, called LILY (Leuven Image processing Library), that was developed for the consortium by our laboratory. There- fore, this paper consists of

International Journal of Engineering Research and Technology (IJERT), 2013

https://www.ijert.org/design-development-of-an-image-processing-algorithm-for-automated-visual-inspection-system https://www.ijert.org/research/design-development-of-an-image-processing-algorithm-for-automated-visual-inspection-system-IJERTV2IS100446.pdf Automated Visual Inspection is an important solution for manufacturing industries to decrease the investment in the inspection process for manufactured product. By the help of vision system the inspection process of the product is conduct, there is an increment in production rate and decrement in the required labour. This research article is described to design and development of an image processing algorithm using MATLAB® software that can help to reduce the defect detection time and compensate for variation in the product for different production line. The developed algorithm uses image processing tool box and absolute mean deviation in MATLAB® software.

Industrial Engineering Journal

With current era of the Automobile industry, the product is manually or visually checked by using check list there is difficulty in inspection due to dependence on human skills and lack of ergonomic applications which cause fatigue. Inspection is one of the primary segments of the industrial parts production process. Machine vision is a present day strategy to inspect produced parts and it is a subcategory of engineering machinery, dealing with issues of information technology, optics, mechanics and industrial automation. Machine vision systems are used increasingly to solve problems of industrial inspection. This paper introduces an automatic vision based defect inspection or detection and dimensional measurement. The system identifies defects (Part Miss, Part Location, Welding Defects and grinding defects etc.) which usually occur in an assembly Structure component. The image processing technique used for Defect detection and algorithms developed for defect detection and linear dimension measurement. Various types of sensors were interfaced with the vision hardware and the part handling mechanism, to complete the total automated vision based inspection system. This system is an accurate, repeatable, fast and cheap solution for industries. This image processing technique is finished utilizing MATLAB programming. This work presents a strategy which decreases the manual work.

Journal of Electronic Imaging, 2011

1979

Real-Time Imaging, 2000

T exture analysis plays an important role in the automated visual inspection of textured images to detect their defects. For this purpose, model-based and feature-based methods are implemented and tested for textile images in a laboratory environment. The methods are compared in terms of their success rates in determining the defects. The Markov Random Field model is applied on dierent DSP systems for real-time inspection.

Mechanical Engineering Research, 2011

Industrial inspection is one of the crucial tasks to ensure quality conformance of products. The inspection tasks can be done by using several methods like non-scaled go/not go gauging, measuring instruments, or advanced non-touching tools. In this research visual inspection using a developed optical system is conducted. One of the aims of this research is to design an on line visual inspection system that is capable to test geometrical quality characteristics of 2-D machined products. The design process includes developing an economical optical system to acquire inspected product's images. Image processing tools are utilized to deal with the product image; and extract features of its geometrical characteristics. A neural network-based methodology is developed and applied to decide whether the product conforms to pre-specified tolerances. The results of the developed methodology are compared to some statistics based visual approaches from the literature. The results show the goodness of the system as an automated visual inspection system and prove its superior performance with respect to other methods.

The image processing used for visual inspection and quality control in a serial production is described in this paper. We used the discrete wavelet transform -DWT in our failure detection algorithm. To achieve robustness as well as good sensitivity of the algorithm, we divide the images into segments. The difference of the wavelet coefficients maxima for the given segment for images of the tile with and without defects was used for defect detection. The analysis of detection capabilities is done for different segment sizes, different detection sensitivity levels -DSL and for two orthogonal wavelets.

En: Proceedings of the …, 2001

Nowadays, quality control is an important problem for fabric manufacturers. Typically these operations have been carried out by humans operators. However, this method has numerous drawbacks such as low precision, performance and effectiveness. Therefore, automatic inspection ...