• Journal of the Korean Society for Precision Engineering
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• v.10 no.3
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• pp.81-86
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• 1993

It is well known that the interest on the on-line sensing of tool wear is growing more and more with the aim of controlling machine tools productivity from the point of view of quality. This paper describes the sensing of the amount of flank wear with vision system. To obtain a proper image He-Ne laser generator is used as the lighting source and obtained image is processed with block processing algorithm and morphological image processing method. By means of this system it is possible to evaluate the parameters of tool wear. Experimental tests performed with this system on an NC lathe have shown good performances here described and discussed.

• Korean Journal of Cognitive Science
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• v.31 no.2
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• pp.25-54
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• 2020

While there is no evidence for parafoveal processing in alphabetic languages such as English and Finnish, there is some evidence that morphological information is processed in syllabic languages like Chinese. Korean writing system, Hangul, would be able to provide morphological preview benefit effects since it is an "alphabetic syllabary" which contains both alphabetic and syllabic features. This study explored morphological parafoveal preview benefit effects during reading Korean using irregular verbs, which have phonological and orthographical differences between fundamental and conjugated forms. In the Experiment, the target word was irregular conjugated form, and there were four preview conditions: identical (e.g. 구워), fundamental form (e.g. 굽다), orthographically related (e.g. 굼다), and unrelated control (e.g. 죨어). In the result of study, identical was shortest and morphological, orthographical, unrelated preview were followed. Moreover, measures of first-pass reading of morphological preview were significantly shorter than those of unrelated control preview. This results support the hypothesis of morphological preview benefit effects in Korean. The implications of the results are discussed.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.05a
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• pp.193-199
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• 2002

Analyzing working conditions with shape characteristics of wear debris in a lubricated machine, it can be effect on diagnosis of hydraulic machining system. And it can be recognized that results are processed threshold images of wear debris. But, in order to predict and estimate a working condition of lubricated machine, it is need to analysis a shape characteristic of wear debris and to identify. Therefor, If shape characteristics of wear debris are identified by computer image analysis and the neural network, it is possible to find the cause and effect of wear condition. In this stud)r, wear debris in the lubricant oil are extracted by membrane filter $(0.45{\mu}m)$, and the quantitative value of shape characteristic of wear debris are calculated by the digital image processing. This morphological information are studied and identified by tile artificial neural network. The purpose of this study is to apply morphological characteristic of wear debris to prediction and estimation of working condition in hydraulic machining systems.

• Progress in Medical Physics
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• v.15 no.2
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• pp.70-76
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• 2004

The most important work for early detection of liver cancer and decision of its characteristic and location is good segmentation of a liver region from other abdominal organs. This paper proposes a fully automatic liver segmentation algorithm based on the abdominal morphology characteristic as an easy and efficient method. Multi-modal threshold as pre-processing is peformed and a spine is segmented for finding morphological coordinates of an abdomen. Then the liver region is extracted using C-class maximum a posteriori (MAP) decision and morphological filtering. In order to estimate results of the automatic segmented liver region, area error rate (AER) and correlation coefficients of rotational binary region projection matching (RBRPM) are utilized. Experimental results showed automatic liver segmentation obtained by the proposed algorithm provided strong similarity to manual liver segmentation.

• International Journal of Contents
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• v.13 no.3
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• pp.1-8
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• 2017

Rice plant numbers and density are key factors for yield and quality of rice grains. Precise and properly estimated rice plant numbers and density can assure high yield from rice fields. The main objective of this study was to automatically detect and count rice plants using images of usual field condition from an unmanned aerial vehicle (UAV). We proposed an automatic image processing method based on morphological operation and boundaries of the connected component to count rice plant numbers after transplanting. We converted RGB images to binary images and applied adaptive median filter to remove distortion and noises. Then we applied a morphological operation to the binary image and draw boundaries to the connected component to count rice plants using those images. The result reveals the algorithm can conduct a performance of 89% by the F-measure, corresponding to a Precision of 87% and a Recall of 91%. The best fit image gives a performance of 93% by the F-measure, corresponding to a Precision of 91% and a Recall of 96%. Comparison between the numbers of rice plants detected and counted by the naked eye and the numbers of rice plants found by the proposed method provided viable and acceptable results. The $R^2$ value was approximately 0.893.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1419-1424
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• 1999

In order to implement morphological filters on image processing systems, the size of structuring element must be small due to the architectural constraints of the systems, which requires the decomposition of structuring element into small elements for the filters with large structuring elements. In this paper, an algorithm for decomposition of structuring element with no restriction on the shape and size is developed which enables sub-optimal implementation of any morphological filter on 3X3 pipeline machine. The given structuring element is first decomposed into the union of elements using sequential search procedure, then each element is further decomposed optimally into 3X3 elements, resulting in final sub-optimal 3$\times$3 hybrid decomposition. The proposed algorithm is applied to some structuring elements and the results close to the optimum are obtained.

• Journal of the Korean Society for information Management
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• v.18 no.2
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• pp.105-124
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• 2001

The purpose of this study is to develop a Korean word analysis system, which can improve performance of IRS, based on various methods of word analysis. In this study we focused on maximizing the speed of Korean word analysis, modulizing each functional system and analyzing Korean morpheme precisely. The system, developed in this study, implemented optimal algorithm to increase the speed of word analysis and to verify speed and performance of each subsystem. In addition, the numeral analysis processing was achieved to reduce a system burden by avoiding recursive analysis of compound nouns, based on numeral pattern recognition.

• Journal of KIISE
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• v.42 no.1
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• pp.68-75
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• 2015

This paper proposes a method for the automatic word spacing of unsegmented Korean sentences. In our method, eojeol monograms are used for word spacing as opposed to the syllable n-grams that have been used in previous studies. The use of a Korean morphological analyzer is limited to the correction of typical word spacing errors. Our method gives a 98.06% syllable accuracy and a 94.15% eojeol recall, when 10-fold cross-validated with the Sejong corpus, after filtering out non-hangul eojeols. The processing rate is 250K eojeols or 1.8 MB per second on a typical personal computer. Syllable accuracy and eojeol recall are related to the size of the eojeol dictionary, better performance is expected with a bigger corpus.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.191-199
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• 2009

In this paper we present a light weighted robust Korean morphological analyzer for mobile devices such as mobile phones, smart phones, and PDA phones. Such mobile devices are not suitable for natural language interfaces for their low CPU performance and memory restriction. In order to overcome the difficulties we propose 1) an online analysis by using Key Event Handler mechanism, 2) and a robust analysis of the Korean sentences with spacing errors without its correction pre-processing. We adapt the proposed Korean analyzer to a Korean-English mobile translator, which shows 5.8% memory usage reduction and 19.0% enhancement of average response time.

• Dementia and Neurocognitive Disorders
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• v.21 no.1
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• pp.17-29
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• 2022

Background and Purpose: Verbal and nonverbal fluency tests are the conventional methods for examining executive function in the elderly population. However, differences in impairments result in fluency tests in patients with mild cognitive impairments (MCIs) and Alzheimer's disease (AD) and in neural correlates underlying the tests still necessitate concrete evidence. Methods: We compared the test performances in 27 normal controls, 28 patients with MCI, and 20 with AD, and investigated morphological changes in association with the test performances using structural magnetic imaging. Results: Patients with AD performed poorly across all the fluency tests, and a receiver operating characteristics curve analysis revealed that only category fluency test discriminated all the 3 groups. Association, category, and design fluency tests involved temporal and frontal regions, while letter fluency involved the cerebellum and caudate. Conclusions: Category fluency is a reliable measure for screening patients with AD and MCI, and this efficacy might be related to morphological correlates that underlie semantic and executive processing.