• 한국항해학회지
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• 제13권1호
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• pp.11-20
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• 1989

Radar image data were collected through the on-line data acquisition system of A/D converter and personal computer, and the image was restorated on CRT or plotter after digital image processing of the data. The digital image processing system which was developed for this study, consisted of some kinds of software as follows : rearrangement, transformation, and enhancement of the image data in real space or frequency space by Fourier transform, edge detection of the image, compact processing, state inferential processing, and so on. Since the image of PPI radar sweeps from the center to the circumference of a circle, the image within a given period has the shape of fan. Therefore the acquired data were transformed to have the same interval as that of data in outmost concentricity. The results of various image processing methods using transformed data were better than those of the methods using original data.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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• pp.56-62
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• 2004

This research attempts to suggest a detecting method for cutting position of an object using the neural network, which is one of intellectual methods, and the digital image processing method. The extraction method of object information using the image data obtained from the CCD camera as a replacement of traditional analog sensor thanks to the development of digital image processing. Accordingly, this research determines the threshold value in binary-coding of an input image with the help of image processing method and the neural network for the real-time gray-leveled input image in substitution for lighting; as a result, a specific position is detected from the processed binary-coded image and an actual system designed is suggested as an example.

• Journal of Biosystems Engineering
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• 제28권5호
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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%.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.536-539
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• 2002

In this paper, we developed the automatic optical fiber aligner by image processing and automatic loading system. Optical fiber is indispensable for optical communication systems that transmit large volumes of data at high speed, but super-precision technology in sub-micron units is required for optical axis adjustment, we have developed 6-axis micro stage system for I/O optical fiber arrays, the initial automatic aligning system/software for a input optical array by the image processing technique, fast I/O-synchronous aligning strategy, the automatic loading/unloading system and the automatic UV bonding mechanism. In order to adjust the alignment it used on PC based motion controller, a $10\mu\textrm{mm}$ repeat-detailed drawing of automatic loading system is developed by a primary line up for high detailed drawing. Also, at this researches used the image processing system and algorithm instead of the existing a primary hand-line up. and fiber input array and waveguide chip formed in line by automatic. Therefore, the developed and manufactured optical aligning system in this research fulfills the great role of support industry for major electronics manufacturers, telecommunications companies, universities, government agencies and other research institutions.

• International journal of advanced smart convergence
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• 제4권2호
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• pp.84-93
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• 2015

This study is for the development of Cover Glass Grinding Processing System. This system is developed for manufacturing a mass product system grinding cover glasses with highly precise mechanism, and we improved resulted quality. In the development process, we developed a complete process technology through mechanical design, image processing technology, spindle control, mark identification algorithm etc. With this cover glass grinding development, we could developed process technology, image processing technology, organization mechanisms and control algorithms.

• IEIE Transactions on Smart Processing and Computing
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• 제6권2호
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• pp.85-92
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• 2017

This paper presents a dehazing method based on a fuzzy membership function and variational method. The proposed algorithm consists of three steps: i) estimate transmission through a pixel-based operation using a fuzzy membership function, ii) refine the transmission using an L1-norm-based regularization method, and iii) obtain the result of haze removal based on a hazy image formation model using the refined transmission. In order to prevent color distortion of the sky region seen in conventional methods, we use a trapezoid-type fuzzy membership function. The proposed method acquires high-quality images without halo artifacts and loss of color contrast.

• 한국철도학회:학술대회논문집
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• 한국철도학회 1998년도 추계학술대회 논문집
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• pp.595-600
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• 1998

Train wheels tend to wear abrasion due to frequent Starlings and brakings. They are important factors of train safety and noise. However, it is difficult and inaccurate to measure their shape and profile manually. Profile measurement system of train wheel with image processing is proposed. The system consists of CCD cameras, PCI image grabber board, and PC operated on Windows '95. Image processing algorithms such as filtering, histogram equalization, and edge detection are presented, and some processing results are illustrated.

• 대한전자공학회논문지
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• 제24권2호
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• pp.315-323
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• 1987

Generally, general-purpose image processing system is so expensive that not so many users easily can access the system. In this paper attemps have been made to design and describe a general and economical image processing system for real-time aplications such as image data compression, pattern recognition and target tracking. The system comprises an operator console, image data acquisition/display sistem and IBM PC/XT. The system also utilizes a high speed Fairchild 16-bit microprocessor with ALU speed of 375 nsec for system control, algrithm execution and user computation. The system also can digitize /display a 256x 256x 8 bit image in real time and store two frames of images. All image pixels are directly accessible by the microprocessor for fast and efficient computation. Some experimental and illustrative results such as target tracking are presented to show the efficient performance of the system.

• Smart Structures and Systems
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• 제17권6호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권8호
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• pp.2881-2894
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• 2014

In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.