• Journal of Institute of Control, Robotics and Systems
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• v.6 no.6
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• pp.492-499
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• 2000

In this paper, realization techniques of the parallel processing and the parallel network system for image processing are described. The parallel image processing system is constructed by the characterization of image processing and processor. Several problems are solved to achieve effective parallel processing and processor networking with the particular properties of image processing, which are reduction of communication quantity, equalization of load and delay depreciation on communication. A parallel image input device is developed for the flexible networking of parallel image processing. An abnormal region detection algorithm which is the basic function in machine vision is applied to evaluate the constructed parallel image processing system. The performance and effectiveness of the system are confirmed by experiments.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.110-113
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• 2003

In this paper, the multi-channel high speed data acquisition system is implemented. This high speed signal processing system for 3-D image display is applicable to the manipulation of a medical image processing, multimedia data and various fields of digital image processing. In order to convert the analog signal into digital one, A/D conversion circuit is designed. PCI interface method is designed and implemented, which is capable of transmission a large amount of data to computer. In order to, especially, channel extendibility of images acquisition, bus communication method is selected. By using this bus method, we can interface each module effectively. In this paper, 32-channel A/D conversion and PCI interface system for 3-dimensional and real-time display of the retina image is developed. The 32-channel image acquisition system and high speed data transmission system developed in this paper is applicable to not only medical image processing as 3-D representation of retina image but also various fields of industrial image processing in which the multi-point realtime image acquisition system is needed.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.526-529
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• 2007

Due to its inherent feature of high-resolution satellite, there is strong need in some specific area to minimize the processing time required to get a standard image on hand from downlink signal acquisition. However, in general image processing system, it takes considerable time to get image data up to certain level from raw data acquisition because the huge amount of data is dealt sequentially as input data. This paper introduces the high-speed image processing system which generates the image data only for the area selected by user. To achieve the high speed performance, this system includes Quick Look Image display function with sampling, ROI selection function, Image Line Index function, and Distributed processing function. The developed RPS was applied to KOMPSAT-2 320Mbps downlink channel and its effectiveness was successfully demonstrated. This feature to provide the image product very quickly is expected to promote the application of high resolution satellite image.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.225-228
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• 2003

The purpose of this paper is to develop a semi -automated system for medical image processing with which tissues or organs from medical images can be segmented and classified by people who have basic knowledge of image processing. In addition, the proposed medical image processing system is independent on types of human tissues or images. In this paper, a new semi-automated image processing system with essential image processing functions for medical images is introduced

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.53-58
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• 2001

In this paper, a low price ultrasound image processing system is developed using DSP and PC. Ultrasound for image is generated by the 32-channel transducer. Ultrasound image is captured by DSP instead of the private image grabber board. Display of image and image processing algorithms are performed by PC. The image processing algorithms based on GUI are realized by software. So users without knowledge of image processing can perform the image enhancement more easily.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.498-506
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• 2003

A computer vision system applied to an intelligent safety vehicle has been required to be worked on a small sized real time special purposed hardware not on a general purposed computer. In addition, the system should have a high reliability even under the adverse road traffic environment. This paper presents a design and an implementation of an onboard hardware system taking into account for high speed image processing to analyze a road traffic scene. The system is mainly composed of two parts: an early processing module of FPGA and a postprocessing module of DSP. The early processing module is designed to extract several image primitives such as the intensity of a gray level image and edge attributes in a real-time Especially, the module is optimized for the Sobel edge operation. The postprocessing module of DSP utilizes the image features from the early processing module for making image understanding or image analysis of a road traffic scene. The performance of the proposed system is evaluated by an experiment of a lane-related information extraction. The experiment shows the successful results of image processing speed of twenty-five frames of 320$\times$240 pixels per second.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.27-31
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• 2005

Vehicle detector system based on image processing technology is a significant domain of ITS (Intelligent Transportation System) applications due to its advantages such as low installation cost and it does not obstruct traffic during the installation of vehicle detection systems on the road[1]. In this paper, we propose architecture for vehicle detection by using image processing. The architecture consists of two main parts such as an image processing part, using high speed FPGA, decision and calculation part using CPU. The CPU part takes care of total system control and synthetic decision of vehicle detection. The FPGA part assumes charge of input and output image using video encoder and decoder, image classification and image memory control.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.4
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• pp.240-250
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• 1988

This pc-vision system digitizes/displays 512*512*8 bit pixel image in real time and is capable of the various image processing. This system provides a versatile solution to those users pursuing high performance image processing system compatible with the VME bus, and is general purpose imaging system giving the optimal efficiency for machine vision, medical use and various task. In this paper, Image processing technique has classified image enhancement and image analysis in order to design and implement the pc-vision system. In order to improve processing speed, This system unilizing ROI processing performs point operation, local operation and global operation as well as common arithmetic/logic operation in real time.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1197-1199
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• 2003

ROCSAT-2 mission is to daily image over Taiwan and the surrounding area for disaster monitoring, land use, and ocean surveillance during the 5-year mission lifetime. The satellite will be launched in December 2003 into its mission orbit, which is selected as a 14 rev/day repetitive Sun-synchronous orbit descending over (120 deg E, 24 deg N) and 9:45 a.m. over the equator with the minimum eccentricity. National Space Program Office (NSPO) is developing a ROCSAT-2 Image Processing System (IPS), which aims to provide real-time high quality image data for ROCSAT-2 mission. A simulated ROCSAT-2 image, based on Level 1B QuickBird Data, is generated for IPS verification. The test image is comprised of one panchromatic data and four multispectral data. The qualification process consists of four procedures: (a) QuickBird image processing, (b) generation of simulated ROCSAT-2 image in Generic Raw Level Data (GERALD) format, (c) ROCSAT-2 image processing, and (d) geometric error analysis. QuickBird standard photogrammetric parameters of a camera that models the imaging and optical system is used to calculate the latitude and longitude of each line and sample. The backward (inverse model) approach is applied to find the relationship between geodetic coordinate system (latitude, longitude) and image coordinate system (line, sample). The bilinear resampling method is used to generate the test image. Ground control points are used to evaluate the error for data processing. The data processing contains various coordinate system transformations using attitude quaternion and orbit elements. Through the qualification test process, it is verified that the IPS is capable of handling high-resolution image data with the accuracy of Level 2 processing within 500 m.

• Journal of Biosystems Engineering
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• v.26 no.3
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• pp.279-286
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• 2001

The purpose of this study were to organize a sorting system, to develop an algorithm of image processing for the shape sorting, and to finally develop a scientific and objective shape sorting system of Korean Red-Ginseng for mechanization of the shape sorting. The results of this study are followed. 1. The shape sorting system of Korean Red-Ginseng consists of a control computer, a color CCD camera(WV-CP4110) for image processing, an image processing board(DT3153), and an image acquisition unit. 2. Many image processing skill, such as sliding, stretching, threshold, binary and D$\sub$t/ were used to analyze the shape sorting factors of Korean Red-ginseng. 3. The sorting accuracy of the shape sorting system for the Korean Red-Ginseng was 74.7%. It is 21.1% lower than that of human inspector. Although the system has low accuracy, using more cameras may improve its sorting accuracy.