• 전기의세계
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• v.30 no.12
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• pp.793-796
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• 1981

최근 우리나라에도 digital image processing에 대한 연구가 활발이 진행되고 있다. 또한 digital image processing의 생체공학에의 응용도 괄목할 만하다. 이러한 연구와 응용에 도움이 되고자 microcomputer를 이용한 image processor설계의 실례를 기술하고자 한다. 이 설계는 목적 image를 stationary image로 가정하여 TV카메라의 영상신호를 sample하여 computer 기억장치에 저장하므로 가격이 저렴하게 된다. 이러한 장치로서는 DMA연결 (Direct Memory Access interface)을 사용하여 빠른 data transfer를 달성할 수 있다. Digital image processing계는 기본적으로 microcomputer가 TV카메라와 TV모니터에 연결된 구조를 하고 있다. Computer가 기억장치에 저장된 data를 처리하여 필요한 정보를 얻게 된다. 이러한 data 처리를 하므로서 image를 사용자가 해석하기 쉽도록 image질을 향상시키거나 computer가 image를 인식하게 한다. 이와같이 처리된 image는 TV모니터를 통해서 볼 수 있다. 본지에서는 256x256개의 pixel들로 이루어지고, 각개의 pixel은 4개의 bit로 구성된 image processor의 설계를 기술한다.

• Smart Structures and Systems
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• v.17 no.6
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• Journal of Biosystems Engineering
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• v.25 no.5
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• pp.409-414
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• 2000

A machine vision system was built to obtain single stationary image from an egg. This system includes a CCD camera, an image processing board and a lighting system. A computer program was written to acquire, enhance and get histogram from an image. To minimize the evaluation time, the artificial neural network with the histogram of the image was used for eggshell evaluation. Various artificial neural networks with different parameters were trained and tested. The best network(64-50-1 and 128-10-1) showed an accuracy of 87.5% in evaluating eggshell. The comparison test for the elapsed processing time per an egg spent by this method(image processing and artificial neural network) and by the processing time per an egg spent by this method(image processing and artificial neural network) and by the previous method(image processing only) revealed that it was reduced to about a half(5.5s from 10.6s) in case of cracked eggs and was reduced to about one-fifth(5.5s from 21.1s) in case of normal eggs. This indicates that a fast eggshell evaluation system can be developed by using machine vision and artificial neural network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.359-360
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• 2021

The pixel-based processing of an image refers to a process of converting a value of one pixel only depending on the value of the current pixel, regardless of the value of another pixel. Pixel-based processing is used as the most basic operation in many fields such as image conversion, image enhancement, and image synthesis. There are processing methods such as arithmetic operation, histogram smoothing, and contrast stretching. In this paper, in order to clearly distinguish the tidal flat region from the tidal flat image of the west coast taken with a drone, we seek a method to find an efficient outline using pixel-based processing in the boundary detection part of the pre-processing process.

• Journal of the Korea Furniture Society
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• v.12 no.1
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• pp.27-37
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• 2001

Automation of wood processing is strongly required to improve the productivity and quality of wood products in wood industry which is one of the most labor-intensive industries. Classification of surface defects on wood boards such as knots is one of the important steps towards a completely automated wood processing system. In this study the possibility of detection of knots by image processing technique was investigated. Algorithm for the automatic determination of threshold value was developed to enhance the flexibility of image processing system. Two different approaches, grid method and tile method, were developed to enhance the speed in extracting features from images. Grid method showed slightly higher processing speed and tile method proved much more stable in determining threshold values. Tile size of $5{\times}5$ pixels or $6{\times}6$ pixels was found to be proper to get stable results with resonable processing time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.87-92
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• 2011

Server overload is directly proportional to requested image data size in a image processing. If request data are increase then system is overloaded in a image processing system. For the reduce of server bottle neck, we will be able to consider a distributed processing. Simple distributed processing system can solve server bottleneck and system overload but high cost system requirements. In this paper, Proposes a new distributed image processing system. Object activation technology are being grafted on to simple distributed processing system. It can optimize the user of system resources and can reuse idle system resources in network.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.178-184
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• 2004

In this paper, we designed an image processing system for the high speed line-scan camera which adopts the new memory model we proposed. As a resolution and a data rate of the line-scan camera are becoming higher, the faster image processing systems are needed. But many conventional systems are not sufficient to process the image data from the line-scan camera during a very short time. We designed the memory controller which eliminates the time for transferring image data from the line-scan camera to the main memory with high-speed SRAM and has a dual-port configuration therefore the DSP can access the main memory even though the memory controller are writing the image data. The memory controller is implemented by VHDL and Xilinx SPARTAN-IIE FPGA.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.6
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• pp.339-344
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• 2013

This paper presents an automatic focal length estimation method to correct the fisheye lens distortion in a spatially adaptive manner. The proposed method estimates the focal length of the fisheye lens by generating two reference focal lengths. The distorted fisheye lens image is finally corrected using the orthographic projection model. The experimental results showed that the proposed focal length estimation method is more accurate than existing methods in terms of the loss rate.

• Journal of Biosystems Engineering
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• v.28 no.5
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• pp.439-448
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• 2003

An image processing algorithm was developed for a robot system which was used in gene study. The robot system achieved a job of colony picking. The colony included DNA of an organism. The robot picked up the colony in petri-dish, which included the cultivated colony in medium, by a picking pin, and moved the colony to wellplates. The vision system consisted of an image acquisition system which acquired the image information of colony, an illumination device which irradiated the object once when it got the image of it, a computer and so on. The image processing algorithm distinguished the colony and detected colony positions. Performance test of the developed algorithm showed that the distinguishing success rate of colony and detecting success rate of colony positions were over 96%.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.1
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• pp.26-33
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• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pas- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this prediction system was acquired $\pm$3.2% error range.