• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.684-689
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• 2005

In this paper, we propose car license plate recognition using morphological information and an enhanced neural network. Morphological information on horizontal and vertical edges was used to extract the license plate from a car image. We used a contour tracking algorithm combined with the method of histogram and location information to extract individual characters in the extracted plate. The enhanced neural network is proposed for recognizing them, which has the method of combining the ART-1 and the supervised teaming method. The proposed method has applied to real world car images. The experimental results show that the proposed method has better the extraction rates than the methods with information of the thresholding, the RGB and the HSI, respectively. And the proposed neural network has better recognition performance than the conventional neural networks.

• Journal of Korea Spatial Information System Society
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• v.1 no.1 s.1
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• pp.49-55
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• 1999

Extracting information of maps is necessary to establish the GIS. In this paper, a house recognition method on the scanned topographic map is described. A contour detection method is used to extract houses from the scanned maps and RLE (run-length encoding) method is used for manipulating houses touching grid lines. To handle houses touched to roads and borderlines, morphological operation is used. To remove misrecognition occurred by morphological operation, the legions which contain characters on the map are also automatically eliminated.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.358-380
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• 2016

In order to considerably reduce the ambiguity rate, we propose in this article a disambiguation approach that is based on the selection of the right diacritics at different analysis levels. This hybrid approach combines a linguistic approach with a multi-criteria decision one and could be considered as an alternative choice to solve the morpho-lexical ambiguity problem regardless of the diacritics rate of the processed text. As to its evaluation, we tried the disambiguation on the online Alkhalil morphological analyzer (the proposed approach can be used on any morphological analyzer of the Arabic language) and obtained encouraging results with an F-measure of more than 80%.

• Korean Journal of Ecology and Environment
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• v.54 no.2
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• pp.125-129
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• 2021

Chironomids are a large group of invertebrates that live in various aquatic habitats. The distribution range of these invertebrates has become varied due to anthropogenic impacts; as such, their distribution can be used as an indicator of environmental health. Adult chironomids are well known in South Korea; however, the larvae have rarely been studied due to difficulties associated with morphological classification. To address this lack of information, we collected larvae from four important rivers in South Korea and summarized their taxonomic morphological characteristics. The antennae, mandible, and mentum were used for larval taxonomic characterization. In this study, we describe the basic morphological features and key pictorial features of 20 species of chironomids, representing 16 genera.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.6
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• pp.899-908
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• 1995

In this paper, the probabilistic relations of dual morphological operations, such as dilation and erosion, closing and opening, and close- open and open-close, and the statistical properties for a continuous stationary lst order Gauss-Markov source are analyzed. The result is that the dual filters have symmetrical means and skews, and equal variances. Also, the statistics of morphological filters are very similar with those of input source, as correlation coefficient increases.

• ETRI Journal
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• v.28 no.6
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• pp.803-806
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• 2006

This letter addresses a structural disambiguation method for Korean adverbs based on the correlative relation constraints between adverbs and modifiees, and the morphological context information of sentences. Using the proposed method, we improved the dependency parsing accuracy of adverbs from 79.2 to 89%. The experimental result shows that the proposed method is especially expert in parsing adverbs which can modify multiple word classes or have a long distance dependency relation to their modifiees.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.173-183
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• 2003

Morphological analysis is the most widely used method for extracting nouns from Korean texts. For every Eojeol, in order to extract nouns from it, a morphological analyzer performs frequent dictionary lookup and applies many morphonological rules, therefore it requires many operations. Moreover, a morphological analyzer generates all the possible morphological interpretations (sequences of morphemes) of a given Eojeol, which may by unnecessary from the noun extraction`s point of view. To reduce unnecessary computation of morphological analysis from the noun extraction`s point of view, this paper proposes a method for Korean noun extraction considering noun occurrence characteristics. Noun patterns denote conditions on which nouns are included in an Eojeol or not, which are positive cues or negative cues, respectively. When using the exclusive information as the negative cues, it is possible to reduce the search space of morphological analysis by ignoring Eojeols not including nouns. Post-noun syllable sequences(PNSS) as the positive cues can simply extract nouns by checking the part of the Eojeol preceding the PNSS and can guess unknown nouns. In addition, morphonological information is used instead of many morphonological rules in order to recover the lexical form from its altered surface form. Experimental results show that the proposed method can speed up without losing accuracy compared with other systems based on morphological analysis.

• The Korea Journal of Herbology
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• v.37 no.5
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• pp.9-16
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• 2022

Objectives : The purpose of this study is to report that applying the genetic discrimination method to Pinelliae Tuber is suitable as a countermeasure for the limitations of morphological identification announced publicly in the Ministry of Food and Drug Safety(MFDS). Methods : Randomly selected fifty samples in Pinelliae Tuber imported from China were used for morphological and genetic identification. The morphological identification was applied method announced publicly by the MFDS. The traits of morphological identification were classified as Pinellia ternata, P. tripartita, Pinellia pedatisecta, and Typhonium flagelliforme, according to the formation of tuberous root and tuber morphology. The genetic identifications were conducted by Sequence Characterized Amplified Region(SCAR) marker and DNA barcoding analysis for cross-validation, respectively. SCAR marker was verified according to the presence or absence of amplicon through PCR amplification using species-specific primers. DNA barcoding analysis used sequence information of the matK region. Results : As a result of the morphological identification, 27 out of 50 samples were identified as original species 'P. ternata' of genuine 'Pinelliae Tuber', and 23 were identified as adulterant species 'P. pedatisecta'. Unlike this, the genetic identification was identified as the original species 'P. ternata' in all 50 samples in the SCAR marker and matK regional sequence analysis. Conclusions : Pinelliae Tuber of morphological mutant that can not be classified by morphological identification is imported from China. The SCAR marker would be used as accurate and efficient assays for species identification of the morphological mutant.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.89-99
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• 2004

This paper proposes a morphological analysis method that enables morphological analysis by checking conditions between two adjacent morphemes. These conditions are fed from a dictionary. This method eliminates a code conversion module and the application of transformational rules for candidate generation. The method claims that very high speed morphological analysis is attainable through simple bit operations for adjacency condition check. MACH, an implementation of the proposed method, is a supersonic Korean morphological analyzer which is able to analyze a document of 1 GB in 5 minutes on a PC with 1.13 GHz Pentium III CPU. The analysis accuracy of MACH is 99.2 %.

• Journal of KIISE
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• v.41 no.9
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• pp.642-651
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• 2014

This paper proposes three probabilistic models for syllable-based Korean morphological analysis, and presents the performance of proposed probabilistic models. Probabilities for the models are acquired from POS-tagged corpus. The result of 10-fold cross-validation experiments shows that 98.3% answer inclusion rate is achieved when trained with Sejong POS-tagged corpus of 10 million eojeols. In our models, POS tags are assigned to each syllable before spelling recovery and morpheme generation, which enables more efficient morphological analysis than the previous probabilistic models where spelling recovery is performed at the first stage. This efficiency gains the speed-up of morphological analysis. Experiments show that morphological analysis is performed at the rate of 147K eojeols per second, which is almost 174 times faster than the previous probabilistic models for Korean morphology.