• Proceedings of the KSPS conference
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• 2002.11a
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• pp.97-100
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• 2002

The purpose of this paper is to investigate the unit of neighbor of Korean words. In English, a word's orthographic neighborhood is defined as the set of words that can be created by changing one letter of the word while preserving letter positions. For example, the words like pike, pole, and tile are all orthographic neighbors of the word 'pile'. In this study, 2 experiments were performed. In these experiments, 4 conditions of prime were included: primes sharing first letter of first syllable(1), first syllable(2), first syllable and the first letter of second syllable with target(3) and with no formal similarity with target(4). In Exp.1, RT was shortest in condition 3. In Exp.2, condition 2 had the shortest RT. We came to the conclusion that in Korean, a word's neighbor is words that share at least one syllable with the word.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1391-1394
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• 1997

This paper proposes a new image processing algorithm to recognize korean documents. It take out the region of text area form input image, then it makes esgmentation of lines, words and characters in the text. A precision segmentation is very important to recognize the input document. The input image has 8-bit gray scaled resolution. Not only the histogram but also brightness dispersion graph are used for segmentation. The result shows a higher accuracy of document recognition.

• Korean Journal of Cognitive Science
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• v.6 no.1
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• pp.47-71
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• 1995

A psychological disturbance caused by letters in double image was termed as'letter sickness'.The effects of stimulus exposure time and letter familiarity on the letter sickness were measured to test a hypothesis that disturbances in eye movement and recognition stages is the cause of letter sickness.Letter sickness incteased significantly as stimulus exposure time lengthened from 50ms,100ms,to 3000ms.It was also significantly higher with familiar Hangul letters as compared with less familiar foreign letters and meaningless words as compared with meaningful words,respectively.These experimental findings imply that letter sickness is caused by the failure of adjusting eye movements to dismiss the double images.that the more familiar the letters.the more strongly the letter-identification process is commotted,resulting in the increased effect of disturbance from double image.and that the disturbance effect of double image is amplified when it is hard to extract the meaning from familiar letters.An experiment where subjects were made to learn Braille-like symbols consisting of 6 dots to test the hypothesis that the stronger the tendency to process the meaning of a symbol,the stronger becomes letter sickness due to double image,also showed that letter sickness significantly increased as a function of learning.

• Korean Journal of Cognitive Science
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• v.27 no.2
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• pp.325-353
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• 2016

The visual span refers to the number of letters that can be accurately recognized without moving one's eyes. The size of the visual span is affected by sensory factors such as perimetric complexity, crowding, and mislocation of letters. Korean Hangul utilizes rather unique alphabetic-syllabary writing system, quite different from English and Chinese writing systems. Due to this combinatorial nature of the script, the visual span for Hangul characters can also be affected by the letter type (e.g., CV vs CVCC). The present study examined the effect of syllable complexity on the visual span for Hangul by comparing letter recognition accuracy across four letter type conditions (C only, CV, CVC, and CVCC). We also aimed to determine the meaningful letter type(s) that is associated with differences in reading abilities in Korean. Using a trigram presentation method, we found that overall recognition accuracy declined as syllable complexity increased. However, the visual span for CVC type was greater than that for CV type, suggesting that the effect is not necessarily linear, and that there might be other factors affecting the visual span for these types of letters. C and CV type showed fairly strong positive correlations with reading comprehension, suggesting that these might be the meaningful units for measuring visual span in relating to reading abilities.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.145-148
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• 2000

This paper proposes a character segmentation method for Korean letter address image. The poor quality of image binarization results in broken character strokes. To overcome this problem, two steps of processing ate introduced. The first one is to merge broken characters to generate character candidates, and the other one is to reduce the complexity of segmentation graph path. These two steps do not use recognition information to keep in high-speed.

• Korean Journal of Cognitive Science
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• v.15 no.1
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• pp.35-41
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• 2004

The letter delay task using monosyllabic words has been employed in order to investigate whether Korean word is processed by the phonological route, and to investigate which stage this phonological information affects word recognition. Two main conditions were delaying a sounding letter( $\rightarrow$향), and delaying a silent letter( $\rightarrow$양). Experiment 1 was the naming task with the SOAs of 150㎳ and 250㎳ in order to investigate whether the phonological information affects the early stages, or the later stages of word recognition. The results showed that the interaction between the phonological value condition and the presence/absence of the prime was significant under the 150㎳ SOA, but not under 250㎳ SOA. Experiment 2 was conducted in order to generalize the results of Experiment 1 in the lexical decision task. The results showed the similar pattern as the Experiment 1. These experiments indicate that Korean words are processed by the phonological route, and the phonological information plays roles in the early stages of word recognition.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.84-87
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• 2018

Handwritten letter recognition is important for numerous real-world applications and many topics like human-machine interaction, education, entertainment, and more. This paper describes the implementation of a real-time handwritten letters recognition system on a common embedded computer. Recognition is performed using a customized convolutional neural network, which was designed to work with low computational resources such as the Raspberry Pi platform. The experimental results show that the proposed real-time system achieves an outstanding performance in the accuracy rate and the response time for recognition of twenty-six handwritten letters.

• Journal of Platform Technology
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• v.6 no.1
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• pp.3-8
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• 2018

This paper proposes a technique for recognizing online handwritten cursive data obtained by tracing a motion trajectory while a user is in the 3D space based on a convolution neural network (CNN) algorithm. There is a difficulty in recognizing the virtual character input by the user in the 3D space because it includes both the character stroke and the movement stroke. In this paper, we divide syllable into consonant and vowel units by using labeling technique in addition to the result of localizing letter stroke and movement stroke in the previous study. The coordinate information of the separated consonants and vowels are converted into image data, and Korean handwriting recognition was performed using a convolutional neural network. After learning the neural network using 1,680 syllables written by five hand writers, the accuracy is calculated by using the new hand writers who did not participate in the writing of training data. The accuracy of phoneme-based recognition is 98.9% based on convolutional neural network. The proposed method has the advantage of drastically reducing learning data compared to syllable-based learning.

• Journal of the Korean Institute of Telematics and Electronics
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• v.6 no.4
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• pp.8-19
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• 1969

This paper attempts to analyize struture of the Letters for the Purpose of makin grecognition of Han-Gelul printed and described the method of recogniton and design of the optimum system. For the reason of the Consistency of Han-Geul (korean letters) combined with Consonants and vouels, the number of the words used in the daily living is about 2,000words. for this reason the composition of the recognition system is complicated, and therfore, this paper is pursued to recearch to handle the separate way ineach form of Letter between consonant and vouel. and the further description of this paper also indicates us the many parts of savings of elements when the character is extracted as logic system in letter composition.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.480-483
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• 2003

We propose a new framework that aims at multi-purpose image recognition, a difficult task for the conventional rule-based systems. This framework is farmed based on the idea of computer-based learning algorithm. In this research, we introduce the new functions of an additional learning and a knowledge reconstruction on the Fuzzy Inference Neural Network (FINN) (1) to enable the system to accommodate new objects and enhance the accuracy as necessary. We examine the capability of the proposed framework using two examples. The first one is the capital letter recognition task from UCI machine learning repository to estimate the effectiveness of the framework itself, Even though the whole training data was not given in advance, the proposed framework operated with a small loss of accuracy by introducing functions of the additional learning and the knowledge reconstruction. The other is the scenery image recognition. We confirmed that the proposed framework could recognize images with high accuracy and accommodate new object recursively.