• ETRI Journal
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• v.42 no.1
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• pp.101-107
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• 2020

For Korean language processing, morphological analysis is a critical component that requires extensive work. This morphological analysis can be conducted in an end-to-end manner without requiring a complicated feature design using a sequence-to-sequence model. However, the sequence-to-sequence model has a time complexity of O(n²) for an input length n when using the attention mechanism technique for high performance. In this study, we propose a linear-time Korean morphological analysis model using a local monotonic attention mechanism relying on monotonic alignment, which is a characteristic of Korean morphological analysis. The proposed model indicates an extreme improvement in a single threaded environment and a high morphometric F1-measure even for a hard attention model with the elimination of the attention mechanism formula.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1279-1286
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• 2002

Generally, radiologists can fail to detect pulmonary nodules in up to 30%. If an automatic system can inform the radiologists of thelocations of the doubtful nodules in the X-ray chest images, the frequency of mistakenly observed numbers of the nodules can be potentially reduced. This software is using morphological filtering and two feature-extraction techniques. The morphological filtering is the first process, which subsequently adds the operations of erosion and dilation to the original images so that this process can transform the original X-ray chest images into manageable ones. The false-positives are frequently being mistaken as nodules but actually these are not real nodules. The second process is the two feature-extraction techniques which are used to reduce the false-positives. Therefore, this system will make more effective detection of pulmonary nodules by reducing the false-positives when applied to the X-ray chest images which is difficult to get accurate detection.

• Journal of KIISE:Software and Applications
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• v.37 no.12
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• pp.946-950
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• 2010

Many sentiment categorization systems based on machine learning methods use morphological analyzers in order to extract linguistic features from sentences. However, the morphological analyzers do not generally perform well in a customer review domain because online customer reviews include many spacing errors and spelling errors. These low performances of the underlying systems lead to performance decreases of the sentiment categorization systems. To resolve this problem, we propose a feature extraction method based on simple longest matching of Eojeol (a Korean spacing unit) and phoneme patterns. The two kinds of patterns are automatically constructed from a large amount of POS (part-of-speech) tagged corpus. Eojeol patterns consist of Eojeols including content words such as nouns and verbs. Phoneme patterns consist of leading consonant and vowel pairs of predicate words such as verbs and adjectives because spelling errors seldom occur in leading consonants and vowels. To evaluate the proposed method, we implemented a sentiment categorization system using a SVM (Support Vector Machine) as a machine learner. In the experiment with Korean customer reviews, the sentiment categorization system using the proposed method outperformed that using a morphological analyzer as a feature extractor.

• Language and Information
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• v.6 no.2
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• pp.105-128
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• 2002

Morphologically annotated corpora are the basis for many tasks of computational linguistics. Most current approaches use statistically driven methods of morphological analysis, that provide just POS-tags. While this is sufficient for some applications, a rule-based full morphological analysis also yielding lemmatization and segmentation is needed for many others. This work thus aims at 〔1〕 introducing a rule-based Korean morphological analyzer called Kormoran based on the principle of linearity that prohibits any combination of left-to-right or right-to-left analysis or backtracking and then at 〔2〕 showing how it on be used as a POS-tagger by adopting an ordinary technique of preprocessing and also by filtering out irrelevant morpho-syntactic information in analyzed feature structures. It is shown that, besides providing a basis for subsequent syntactic or semantic processing, full morphological analyzers like Kormoran have the greater power of resolving ambiguities than simple POS-taggers. The focus of our present analysis is on Korean text.

• Journal of Korea Multimedia Society
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• v.5 no.1
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• pp.10-17
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• 2002

It is necessary to induce for using mass transit instead of passenger car, which is high occupied roadway. It is necessary to develop the automated enforcement system to do manage such things. There are lots of problems to enforce the exclusive roadway. One of the biggest problem is the difficulty of vehicle classification. In this paper, morphological vehicle classification algorithm is proposed. Vehicle object is separated from background using frame difference, then the proposed unique weighted skeleton feature is extracted. The experiments show that the vehicle identification results produced by weighted skeleton feature seem to be good quality.

• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.15-21
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• 2015

This study proposed a Sasang constitution classification system that can increase the objectivity and reliability of Sasang constitution diagnosis using the image of frontal face, in order to solve problems in the subjective classification of Sasang constitution based on Sasang constitution specialists' experiences. For classification, characteristics indicating the shapes of the eyes, nose, mouth and chin were defined, and such characteristics were extracted using the morphological statistic analysis of face images. Then, Sasang constitution was classified through a SVM (Support Vector Machine) classifier using the extracted characteristics as its input, and according to the results of experiment, the proposed system showed a correct recognition rate of 93.33%. Different from existing systems that designate characteristic points directly, this system showed a high correct recognition rate and therefore it is expected to be useful as a more objective Sasang constitution classification system.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.1-8
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• 2006

Many researchers have been studied for the automatic chromosome karyotype classification and analysis. For the automatic classify the each chromosome which is the image in microscope, it is necessary to process the sub-procedure, ie. image pre-processing, implementing karyotype classifier. The image pre-processing proceeded the each chromosome separation, the noise exception and the feature parameter extraction. The extracted morphological feature parameter were the centromeric index(C.I.), the relative length ratio(R.L.), and the relative area ratio(R.A.). In this paper, the fuzzy classifier was implemented for the human chromosome karyotype classification. The extracted morphological feature parameter were used in the input parameter of fuzzy classifier. We studied about the selection of the membership function for the optimal fuzzy classifier in each chromosome groups.

• ALGAE
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• v.25 no.3
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• pp.115-120
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• 2010

The natural growth of a population of Gomphosphaeria aponina Kutzing (Chroococcales, Cyanoprocaryota) was studied in a cemented freshwater tank in Allahabad, India. This population appeared to be a polymorphic species. Different species of the genus Gomphosphaeria have been segregated based on morphological features of colonies, cells and mucilage. However, these features are not well defined for different species. Our observations revealed many feature variations and, interestingly, certain features that have been described for different Gomphosphaeria species were seen in a single population. In this study, records of such variable morphological features were possible due to the availability of numerous specimens and continuous observations for more than two years. Further, this study revealed two points: (i) more detailed morphological studies are required both from nature as well as in culture to identify critical differences among the species, and (ii) molecular characterization of taxa appears to be necessary for final species settlement.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.535-538
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• 2009

Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise to preserve edges. As the result, MAM of the proposed method enhances the image to about 10% in comparison with Winner filter by Edge Preservation Index and PSNR, and 10% to only adaptive median filtering.

• Journal of IKEEE
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• v.4 no.2 s.7
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• pp.288-294
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• 2000

In this paper, an efficient detail extraction technique for a progressive coding scheme is proposed. The existing technique using the top-hat transformation yields an efficient extraction scheme for isolated and visually important details, but yields an inefficient results containing significant redundancy extracting the contour information. The proposed technique using the strong edge feature extraction property of the morphological Laplacian in this paper can reduce the redundancy, and thus provides lower bit-rate. Experimental results show that the proposed technique is more efficient than the existing one, and promise the applicability of the morphological Laplacian operator.