• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.7-13
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• 2021

Machine vision is a technology that helps the computer as if a person recognizes and determines things. In recent years, as advanced technologies such as optical systems, artificial intelligence and big data advanced in conventional machine vision system became more accurate quality inspection and it increases the manufacturing efficiency. In machine vision systems using deep learning, the image quality of the input image is very important. However, most images obtained in the industrial field for quality inspection typically contain noise. This noise is a major factor in the performance of the machine vision system. Therefore, in order to improve the performance of the machine vision system, it is necessary to eliminate the noise of the image. There are lots of research being done to remove noise from the image. In this paper, we propose an autoencoder based machine vision system to eliminate noise in the image. Through experiment proposed model showed better performance compared to the basic autoencoder model in denoising and image reconstruction capability for MNIST and fashion MNIST data sets.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.22-24
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• 2004

This paper proposes a printing quality inspection system of film-type envelopment. Since the printing system is running at very high-speed (140m/min.) and the line error has very narrow width, we have to choose one-dimensional high-speed and high-resolution line scan camera. The vibration of the printing machine and the illumination environment make the inspection problem more harder. To obtain reliable inspection results, many software image processing techniques are applied and many parameters are tuned. The performance of the proposed system is proved by many simulations and long time real-plant experiments.

• Journal of Ocean Engineering and Technology
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• v.30 no.3
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• pp.194-200
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• 2016

Recently, UUVs (unmanned underwater vehicles) have increasingly been applied in various science and engineering applications. In-water inspection, which used to be performed by human divers, is a potential application for UUVs. In particular, the operational safety and performance of in-water inspection missions can be greatly improved by using an underwater robotic vehicle. The capabilities of hovering maneuvers and automatic image mosaicking are essential for autonomous underwater visual inspection. This paper presents the development of a hover-capable autonomous underwater vehicle system for autonomous in-water inspection, which includes both a hardware platform and operational software algorithms. Some results from an experiment in a model basin are presented to demonstrate the feasibility of the developed system and algorithms.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.126-130
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• 2021

The ball grid array is one of the packaging methods that used in high density printed circuit board. Solder void defects caused by voids in the solder ball during the BGA process do not directly affect the reliability of the product, but it may accelerate the aging of the device on the PCB layer or interface surface depending on its size or location. Void inspection is important because it is related in yields with products. The most important process in the optical inspection of solder void is the segmentation process of solder and void. However, there are several segmentation algorithms for the vision inspection, it is impossible to inspect all of images ideally. When X-Ray images with poor contrast and high level of noise become difficult to perform image processing for vision inspection in terms of software programming. This paper suggests the solution to deal with the suggested problem by means of using Mask R-CNN instead of digital image processing algorithm. Mask R-CNN model can be trained with images pre-processed to increase contrast or alleviate noises. With this process, it provides more efficient system about complex object segmentation than conventional system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.51-56
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• 2000

This study is to implement automatic inspection system of motor body panel by visual system. since it is inefficient to examine adhesion condition of components with the naked eye, image processing algorithm is presented to replace the existing manual inspection process with an automatic inspection process the developed automatic inspection system presents tile examination method of the adhesion condition of components with a pixed camera, which leads to an increase of the productivity and a reduction of manufacturing cost

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.343-348
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• 1992

Using the real-time image processing technique, we have developed an automatic visual inspection system which detects the defects of the surface muonted components in PCB( missing components, mislocation, mismounts, and reverse polarity, etc ) and collects the quality control and production management data. An image processing system based on a commercial parallel processor, TRANSPUTER by which the image processing time can be largely reduced was designed. Analyzing the collected data, the proposed inspection system contributes to the productivity improvement throughthe reduction of defective rate.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.16-21
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• 2015

In this paper, we presented Under Vehicle Inspection System by comparing two image signals. Two signals are generated by license plate number and under-vehicle pattern recognition. The test shows reliable precision within real-time of 2.8sec, which can be applicable commercially. In the future, more research will be conducted to enhance the precision by automatic image balance in many challenging situations.

• Journal of the Semiconductor & Display Technology
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• v.11 no.3
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• pp.39-44
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• 2012

Electronics in modern lives have become more miniaturized and precise. Multi Layered Ceramic Capacitor (MLCC) occupies 50% of electronic components consisting of electronics. This high volume of the production needs high speed and more precise machine performances. The dominate parts of the production equipments are the module transporting components and the visual inspection module. Most visual inspection has been off-line because of the image processing time. In this paper, a new image processing method is proposed to reduce thousands of matrix calculation for image processing and realize on-line high speed inspection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1157-1162
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.1
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• pp.1-11
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• 1997

Austomated visual inspection(AVI) capability has become an important key component in the automated manufacturing system. In such a visual inspection system an intensity(or color) image of a scene is quickly affected by optical property of objects, condition and roughness of surface, lens and filters, image sensor property and lighting system. In particular, the lighting system disign is the most important factor, since it affects overall performance of the visual system. For fast and cheap automated visual inspection system it is important to obtain the good image quality which results from careful attention to the design of the lighting system. In this paper, the lighting subsystem of AVI system is analysed for the inspection of printed circuit board(PCB) patterns. The spectral reflectance of materials, which are composed of PCB, is measured for choosing the light source. The reflection property is theoretically obtained by a reflection model and also obtained by experiments which measure intensity with varying the viewing direction of image sensor and the lighting direction of illuminator. The illumination uniformity of a ring-type illuminator. The lighting system is designed based upon the experimental results and theoretial analysis.