• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.3
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• pp.11-25
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• 2009

Fingerprint sample quality is one of major factors influencing the matching performance of fingerprint recognition systems. The error rates of fingerprint recognition systems can be decreased significantly by removing poor quality fingerprints. The purpose of this paper is to assess the effectiveness of individual sample quality measures on the performance of minutiae-based fingerprint recognition algorithms. Initially, the authors examined the various factors that influenced the matching performance of the minutiae-based fingerprint recognition algorithms. Then, the existing measures for fingerprint sample quality were studied and the more effective quality measures were selected and compared with two image quality software packages, (NFIQ from NIST, and QualityCheck from Aware Inc.) in terms of matching performance of a commercial fingerprint matcher (Verifinger 5.0 from Neurotechnologija). The experimental results over various Fingerprint Verification Competition (FVC) datasets show that even a single sample quality measure can enhance the matching performance effectively.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.101-108
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• 2024

AI-OCR (Artificial Intelligence Optical Character Recognition) combines OCR technology with Artificial Intelligence to overcome limitations that required human intervention. To enhance the performance of AI-OCR, training on diverse data sets is essential. However, the recognition rate declines when image colors have similar brightness levels. To solve this issue, this study employs Homomorphic filtering as a preprocessing step to clearly differentiate color levels, thereby increasing text recognition rates. While Homomorphic filtering is ideal for text extraction because of its ability to adjust the high and low frequency components of an image separately using a gamma value, it has the downside of requiring manual adjustments to the gamma value. This research proposes a range for gamma threshold values based on tests involving image contrast, brightness, and entropy. Experimental results using the proposed range of gamma values in Homomorphic filtering suggest a high likelihood for effective AI-OCR performance.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.2
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• pp.77-87
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• 2024

Purpose : The study aim was to determine the present state of occupational therapists in Korea in terms of the Model of Human Occupation (MOHO). We collected basic data for future research by investigating recognition by occupational therapists for applications of the MOHO and the necessity thereof. Specifically, we explored ways to effectively apply the MOHO in occupational therapy. Methods : We conducted a study from December 3, 2023, to January 18, 2024. A survey was administered to 163 occupational therapists. The general characteristics, recognition, and necessity of the MOHO were examined using a frequency analysis and descriptive statistics. Results : The most responses to "degree of ease of access to the MOHO information" were for "disagree" 56 people(34 %). Regarding "degree of satisfaction with information about [the] MOHO," 53 people (33 %) responded with "disagree" (the highest response rate). Only 22 % had applied the MOHO previously. Second, occupational therapists thought that the MOHO should be applied in occupational therapy clinical practice; they also believed that related education was needed for occupational therapy university/college students and occupational therapists. In response to the question, "What channels do you think MOHO education will be helpful for?", 118 people (32 %) answered "continuing education at the association level," and 86 people (23 %) answered "educational institutions aimed at MOHO." Conclusion : Based on these results, I recommend the following. For application of the MOHO in occupational therapy clinical practice, an occupation-based concept must first be established. In addition, related knowledge must be acquired through the expansion of education regarding the MOHO. The efficient application of the MOHO will ultimately lead to improvement in the health of clients.

• Cartoon and Animation Studies
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• s.40
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• pp.477-496
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• 2015

Emotional awareness is the image of a person is represented by different tendencies. Currently, the emotion computing to objectively evaluate the emotion recognition research is being actively studied. However, existing emotional computing research has many problems to run. First, the non-objective in emotion recognition if it is inaccurate. Second, the correlation between the emotion recognition is unclear points. So to test the regularity of image sensitivity to the need of the present study is to control emotions in the computing system. In addition, the screen number of the emotion recognized for the purpose of this study, applying the method of objective image emotional computing system and compared with a similar degree of emotion of the person. The key features of the image emotional computing system calculates the emotion recognized as numbered digital form. And to study the background of emotion computing is a key advantage of the effect of the James A. Russell for digitization of emotion (Core Affect). Pleasure emotions about the core axis (X axis) of pleasure and displeasure, tension (Y-axis) axis of tension and relaxation of emotion, emotion is applied to the computing research. Emotional axis with associated representative sensibility very happy, excited, elated, happy, contentment, calm, relaxing, quiet, tired, helpless, depressed, sad, angry, stress, anxiety, pieces 16 of tense emotional separated by a sensibility ComputingIt applies. Course of the present study is to use the color of the color key elements of the image computing formula sensitivity, brightness, and saturation applied to the sensitivity property elements. Property and calculating the rate sensitivity factors are applied to the importance weight, measured by free-level sensitivity score (X-axis) and the tension (Y-axis). Emotion won again expanded on the basis of emotion crossed point, and included a representative selection in Sensibility size of the top five ranking representative of the main emotion. In addition, measuring the emotional image of a person with 16 representative emotional score, and separated by a representative of the top five senses. Compare the main representative of the main representatives of Emotion and Sensibility people aware of the sensitivity of the results to verify the similarity degree computing emotion emotional emotions depending on the number of representative matches. The emotional similarity computing results represent the average concordance rate of major sensitivity was 51%, representing 2.5 sensibilities were consistent with the person's emotion recognition. Similar measures were the degree of emotion computing calculation and emotion recognition in this study who were given the objective criteria of the sensitivity calculation. Future research will need to be maintained weight room and the study of the emotional equation of a higher concordance rate improved.

• Journal of agricultural medicine and community health
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• v.30 no.2
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• pp.205-211
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• 2005

Objectives: In Ulleung island, many people was suffered from dermatomycosis. But many patients was not recognized to dermatomycosis due to little symptom. So, public health education was needed. We will plan education direction based on evidence. So, in one way, the recognition level was needed to determine education direction. Methods: From June to July in 2005, 45 patients was made a question. The questionnaire was composed of chief complaint, site, duration, similar disease in family, 5 questiones and so on. If patients was recognized to 1 question, 1 score was added. Remain 4 question was done in same manner. Results: The low score group were that total socre was beyond 2. And The high score group were that total score was above 3. The low score group was 24 persons, average age was 59. The high score group was 21 persons and average age was 42. Male and female ratio was 7 : 17 in low score group and 10 : 11 in high score group. Coinfection was 17 patients in low score group and 2 patients in high score group. There was only 17 patients that wete recognized that dermatomycosis and "Moozom" were same disease. And, many patients was not recognized to possibility of reinfection after treatment of dermatomycosis. Conclusions: In Ulleung island, coinfection rate was higher than other area bacause of low recognition level. And infection rate in family was higher too. So, there was essential to educate of dermatomycosis prevention. Dermatomycosis patient became older and was more female than other area, so there was need to centralize people to be needed of public health education. Finally, many statistical study for dermatomycosis should be needed for many patients and general populations in Ulleung island.

• International journal of advanced smart convergence
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• v.6 no.2
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• pp.59-64
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• 2017

There are three sorts of voices of female vocalists: soprano, mezzo-soprano, and contralto according to the transliteration. Among them, the soprano has the highest vocal range. Since the voice is generated through the human vocal tract based on the voice generation model, it is greatly influenced by the vocal tract. The structure of vocal organs differs from person to person, and the formants characteristic of vocalization differ accordingly. The formant characteristic refers to a characteristic in which a specific frequency band appears distinctly due to resonance occurring in each vocal tract in the vocal process. Formant characteristics include personality that occurs in the throat, jaw, lips, and teeth, as well as phonological properties of phonemes. The first formant is the throat, the second formant is the jaw, the third formant and the fourth formant are caused by the resonance phenomenon in the lips and the teeth. Among them, pronunciation is influenced not only by phonological information but also by jaws, lips and teeth. When the mouth is small or the jaw is stiff when pronouncing, pronunciation becomes unclear. Therefore, the higher the accuracy of the pronunciation characteristics, the more clearly the formant characteristics appear in the grammar spectrum. However, many soprano singers can not open their mouths because their jaws, lips, teeth, and facial muscles are rigid to maintain high tones when singing, which makes the pronunciation unclear and thus the formant characteristics become unclear. In this paper, in order to confirm the accuracy of the pronunciation characteristics of soprano singers, the experimental group was selected as the soprano singers A, B, C, D, E of Korea and analyzed the grammar spectrum and conducted the MOS test for pronunciation recognition. As a result, soprano singer B showed a clear recognition from F1 to F5 and MOS test result showed the highest recognition rate with 4.6 points. Soprano singers A, C, and D appear from F1 to F3, but it was difficult to find formants above 2kHz. Finally, the soprano singer E had difficulty in finding the formant as a whole, and MOS test showed the lowest recognition rate at 2.1 points. Therefore, we confirmed that the soprano singer B, which exhibits the most distinct formant characteristics in the grammar spectrum, has the best pronunciation accuracy.

• Science of Emotion and Sensibility
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• v.20 no.3
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• pp.61-70
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• 2017

Physiological responses have been measured to recognize emotion. Although physiological responses have been interrelated between organs, their connectivities have been less considered for emotion recognizing. The connectivities have been assumed to enhance emotion recognition. Specially, autonomic nervous system is physiologically modulated by the interrelated functioning. Therefore, this study has been tried to analyze connectivities between heart and respiration and to find the significantly connected variables for emotion recognition. The eighteen subjects(10 male, age $24.72{\pm}2.47$) participated in the experiment. The participants were asked to listen to predetermined sound stimuli (arousal, relaxation, negative, positive) for evoking emotion. The bio-signals of heart and respiration were measured according to sound stimuli. HRV (heart rate variability) and BRV (breathing rate variability) spectrum were obtained from spectrum analysis of ECG (electrocardiogram) and RSP (respiration). The synchronization of HRV and BRV spectrum was analyzed according to each emotion. Statistical significance of relationship between them was tested by one-way ANOVA. There were significant relation of synchronization between HRV and BRV spectrum (synchronization of HF: F(3, 68) = 3.605, p = 0.018, ${\eta}^2_p=0.1372$, synchronization of LF: F(3, 68) = 5.075, p = 0.003, ${\eta}^2_p=0.1823$). HF difference of synchronization between ECG and RSP has been able to classify arousal from relaxation (p = 0.008, d = 1.4274) and LF's has negative from positive (p = 0.002, d = 1.7377). Therefore, it was confirmed that the heart and respiration to recognize the dimensional emotion by connectivity.

• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.616-626
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• 2008

The face shape extracted by the depth values has different appearance as the most important facial feature information and the face images decomposed into frequency subband are signified personal features in detail. In this paper, we develop a method for recognizing the range face images by combining the multiple frequency domains for each depth image and depth fusion using fuzzy integral. For the proposed approach, the first step tries to find the nose tip that has a protrusion shape on the face from the extracted face area. It is used as the reference point to normalize for orientated facial pose and extract multiple areas by the depth threshold values. In the second step, we adopt as features for the authentication problem the wavelet coefficient extracted from some wavelet subband to use feature information. The third step of approach concerns the application of eigenface and Linear Discriminant Analysis (LDA) method to reduce the dimension and classify. In the last step, the aggregation of the individual classifiers using the fuzzy integral is explained for extracted coefficient at each resolution level. In the experimental results, using the depth threshold value 60 (DT60) show the highest recognition rate among the regions, and the depth fusion method achieves 98.6% recognition rate, incase of fuzzy integral.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.3
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• pp.249-255
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• 2017

The finger vein recognition technology is a method to acquire a finger vein image by illuminating infrared light to the finger and to authenticate a person through processes such as feature extraction and matching. In order to recognize a finger vein, a 2D mask-based two-dimensional convolution method can be used to detect a finger edge but it takes too much computation time when it is applied to a low cost micro-processor or micro-controller. To solve this problem and improve the recognition rate, this study proposed an extraction method for the region of interest based on virtual core points and moving average filtering based on the threshold and absolute value of difference between pixels without using 2D convolution and 2D masks. To evaluate the performance of the proposed method, 600 finger vein images were used to compare the edge extraction speed and accuracy of ROI extraction between the proposed method and existing methods. The comparison result showed that a processing speed of the proposed method was at least twice faster than those of the existing methods and the accuracy of ROI extraction was 6% higher than those of the existing methods. From the results, the proposed method is expected to have high processing speed and high recognition rate when it is applied to inexpensive microprocessors.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1501-1514
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• 2008

The face shape extracted by the depth values has different appearance as the most important facial information. The face images decomposed into frequency subband are signified personal features in detail. In this paper, we develop a method for recognizing the range face images by multiple frequency domains for each depth image using the modified fuzzy c-mean algorithm. For the proposed approach, the first step tries to find the nose tip that has a protrusion shape on the face from the extracted face area. And the second step takes into consideration of the orientated frontal posture to normalize. Multiple contour line areas which have a different shape for each person are extracted by the depth threshold values from the reference point, nose tip. And then, the frequency component extracted from the wavelet subband can be adopted as feature information for the authentication problems. The third step of approach concerns the application of eigenface to reduce the dimension. And the linear discriminant analysis (LDA) method to improve the classification ability between the similar features is adapted. In the last step, the individual classifiers using the modified fuzzy c-mean method based on the K-NN to initialize the membership degree is explained for extracted coefficient at each resolution level. In the experimental results, using the depth threshold value 60 (DT60) showed the highest recognition rate among the extracted regions, and the proposed classification method achieved 98.3% recognition rate, incase of fuzzy cluster.