• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.587-591
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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 for Noise and Vibration Engineering
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• v.19 no.4
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• pp.335-346
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• 2009

As the economy has grown and the main industry in Korea has been changed from secondary industry to tertiary industry, the importance of indoor environment has been a matter of common concern, in which one of the main concerns is to improve the indoor acoustic conditions. However, even though this is required more than before, there are no measures to protect the human being from the noise of electric home appliances. This is owing to the absence of the data about sound power level of electric home appliances. So, we investigate the sound power level of them and analyze the acoustical characteristics of each one. First, we tried to investigate the sound power measurement method of each electric home appliance. After it we test the sound power level of them. From the survey, we can know that the vacuum cleaner is the most noisy electric home appliance, and the refrigerator is the least noisy one. This results will help us predict the indoor noise level using the basic data of sound power level.