• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.43-48
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• 2017

Semiconductors are leading the development of industrial technology, leading to miniaturization and weight reduction of electronic products as a leading technology, we are dragging the electronic industry market Especially, the semiconductor manufacturing process is composed of highly accurate and complicated processes, and effective production is required Recently, a vision system combining a computer and a camera is utilized for defect detection In addition, the demand for a system for measuring the shape of a fine pattern processed by a special process is rapidly increasing. In this paper, we propose a vision algorithm using mask image to detect scratch defect of semiconductor pockage. When applied to the manufacturing process of semiconductor packages via the proposed system, it is expected that production management can be facilitated, and efficiency of production will be enhanced by failure judgment of high-speed packages.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1201-1208
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• 2020

A mass of seawater with similar properties in the ocean is called a water mass, and the front is a sea area where two masses of different properties meet. The gradient algorithm is a method of extracting where the sea water temperature pixel changes rapidly assuming that the slope is large, and the place with the large slope is assumed to be a front. This method is able to process large amounts of satellite data at once. Therefore, in this study, we tried to find the front lines in the sea area around the Korean Peninsula by using a gradient algorithm. The study data used gridded sea surface temperature satellite data. The resolution was 1/4°, and the monthly average data from January 1993 to December 2018 were used. There were major five fronts representatively, China Coastal Front, South Sea Coastal Front, Kuroshio Front/ Kuroshio Extension Front, Subpolar Front and the Subarctic Front. As a result of comparing the distribution of front by season, more types of front were distributed in winter and spring than in summer and autumn, and the distribution range was wider.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1365-1373
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• 2002

In this paper, we present two types of vision algorithm that mobile robot has CCD camera. for obstacle avoidance. This is simple algorithm that compare with grey level from input images. Also, The mobile robot depend on image processing and move command from PC host. we has been studied self controlled mobile robot system with CCD camera. This system consists of digital signal processor, step motor, RF module and CCD camera. we used wireless RF module for movable command transmitting between robot and host PC. This robot go straight until recognize obstacle from input image that preprocessed by edge detection, converting, thresholding. And it could avoid the obstacle when recognize obstacle by line histogram intensity. Host PC measurement wave from various line histogram each 20 pixel. This histogram is (x, y) value of pixel. For example, first line histogram intensity wave from (0, 0) to (0, 197) and last wave from (280, 0) to (2n, 197. So we find uniform wave region and nonuniform wave region. The period of uniform wave is obstacle region. we guess that algorithm is very useful about moving robot for obstacle avoidance.