• Proceedings of the Acoustical Society of Korea Conference
• /
• 1984.12a
• /
• pp.57-61
• /
• 1984

In this study, the system is proposed which can be used for recognition of Koean single vowles "ㅏ, ㅓ, ㅗ, ㅜ, ㅡ, ㅣ, ㅐ, ㅔ, ㅚ,", and automatic recognition is processed using $\mu$-computer. 3 men of not-being-studied are participated in this experiment. Using the period of vowels, one part of the steady state is selected for high speed recognition, and amplitude comparison method, LPC, PARCOR, and Formant are used for parameter of recognition. Formant is obtained by peak picking method using LPC, and then vowels are recognized by amplitude comparison method, LPC, PARCOR, and Formant. As a result, Recognition rates are 90.1% for amplitude comparison method, 93.1% for LPC, 100% for PARCOR, 88.8% for using formant.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.04a
• /
• pp.470-473
• /
• 2004

In this paper, the comparison of speech feature parameters for emotion recognition is studied for emotion recognition using speech signal. For this purpose, a corpus of emotional speech data recorded and classified according to the emotion using the subjective evaluation were used to make statical feature vectors such as average, standard deviation and maximum value of pitch and energy. MFCC parameters and their derivatives with or without cepstral mean subfraction are also used to evaluate the performance of the conventional pattern matching algorithms. Pitch and energy Parameters were used as a Prosodic information and MFCC Parameters were used as phonetic information. In this paper, In the Experiments, the vector quantization based emotion recognition system is used for speaker and context independent emotion recognition. Experimental results showed that vector quantization based emotion recognizer using MFCC parameters showed better performance than that using the Pitch and energy parameters. The vector quantization based emotion recognizer achieved recognition rates of 73.3％ for the speaker and context independent classification.

• Journal of the Optical Society of Korea
• /
• v.13 no.4
• /
• pp.445-450
• /
• 2009

Fingerprint recognition using a joint transform correlator (JTC) is the most well-known technology among optical fingerprint recognition methods. The JTC method optically compares the reference fingerprint image with the sample fingerprint image then examines match or non-match by acquiring a correlation peak. In contrast to the JTC method, this paper presents a new method to examine fingerprint recognition by producing a computer generated hologram (CGH) of those two fingerprint images and directly comparing them. As a result, we present some parameters to show that fingerprint recognition capability of the CGH direct comparison method is superior to that of the JTC method.

• The Korean Journal of Health Service Management
• /
• v.6 no.4
• /
• pp.267-277
• /
• 2012

The purpose of this descriptive research is to identify the recognition and attitude of college students towards Complementary & Alternative Medicine (CAM). The subjects of the study were 620 students of a junior college in the D metropolitan city. The data was collected from July 2 to July 31, 2012 and SPSS/WIN 18.0 program was used to analyze the data. From the comparison of CAM recognition between the two groups. There were significant differences for each item of CAM recognition. For the attitude on CAM, there were significant differences between the two groups. There needs to be more follow-up studies based on the current study in order to establish the basic data that can help find specific educational methods for the areas of CAM that lack recognition from the students.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.272-277
• /
• 1998

If we want to compare the form of two objects, the human vision takes into account the parameter's width/length/height at the same time. however, the machine needs to compare width then lengths and finally height. In each comparison the machine considers only one character. The goal of this paper is to imitate the human manner of comparison and recognition by using two or three characters instead of one during the comparison. The ellipse is a first approach of comparison because it provides us a general and a simple relation that can link two parameters that are the half axis of the ellipse. Indeed, we assimilate each character to a half axis of the ellipse and the result is a geometrical figure that varies according to values of the two characters.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.04a
• /
• pp.287-292
• /
• 2004

In this study, we made a comparative study of backpropagation neural network and probabilistic neural network and bayesian classifier and perceptron as shape recognition algorithm of welding flaws. For this purpose, variables are applied the same to four algorithms. Here, feature variable is composed of time domain signal itself and frequency domain signal itself, Through this process, we confirmed advantages/disadvantages of four algorithms and identified application methods of few algorithms.

• The Journal of Korea Robotics Society
• /
• v.1 no.2
• /
• pp.151-157
• /
• 2006

This paper is concerned with the template-based face recognition from robot camera images with illumination and distance variations. The approaches used in this paper consist of Eigenface, Fisherface, and Icaface which are the most representative recognition techniques frequently used in conjunction with face recognition. These approaches are based on a popular unsupervised and supervised statistical technique that supports finding useful image representations, respectively. Thus we focus on the performance comparison from robot camera images with unwanted variations. The comprehensive experiments are completed for a databases with illumination and distance variations.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.5
• /
• pp.33-40
• /
• 2004

In this paper, we constructs face database by using wavelet comparison, and compare face recognition rate by using principle component analysis (Principal Component Analysis : PCA) algorithm. General face recognition method constructs database, and do face recognition by using normalized size. Proposed method changes image of normalized size (92${\times}$112) to 1 step, 2 step, 3 steps to wavelet compression and construct database. Input image did compression by wavelet and a face recognition experiment by PCA algorithm. As well as method that is proposed through an experiment reduces existing face image's information, the processing speed improved. Also, original image of proposed method showed recognition rate about 99.05%, 1 step 99.05%, 2 step 98.93%, 3 steps 98.54%, and showed that is possible to do face recognition constructing face database of large quantity.

• Journal of The Korea Institute of Healthcare Architecture
• /
• v.27 no.1
• /
• pp.17-34
• /
• 2021

Purpose: The purpose of this study was to find out the difference in the priority level of recognition for universal design application in public spaces by gender. Method: ANOVA(analysis of variance) and post-hoc test were conducted to determine the priority level of recognition and pattern for the disabled, non-disabled, and experts classified into males and females. Results: There was no gender difference in the comparison by sector for all males and females. However, in comparing of domains and facilities, women showed a higher level of recognition than men in the building sector and cross domain. When comparing space consumers and producers by dividing them into male and female groups, women showed a higher level of recognition than men in producers, but there was no gender difference between consumers. In comparison by sector, domain and facility, women producers also showed a higher level of recognition in the road sector, park and recreation sector, sidewalk domain, four-spaces in the park and recreation sector, and six-spaces in the building sector than men producers. Also, in the building sector, women producers and consumers showed a higher recognition level than men. Comparing the disabled, non-disabled people and experts by dividing them into male and female groups, in the case of non-disabled people and experts, women showed a higher level of recognition than men, while men showed a higher level of recognition than women in the disabled. In addition, there were differences in recognition patterns in many spaces and facilities by gender. Implications: This study is meaningful in comparing the differences in the priority level of recognition and patterns between men and women to apply universal design for people of all ages and both sexes.

• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.2463-2466
• /
• 2003

This paper studied the pattern recognition algorithm and feature parameters for emotion recognition. In this paper, KNN algorithm was used as the pattern matching technique for comparison, and also VQ and GMM were used lot speaker and context independent recognition. The speech parameters used as the feature are pitch, energy, MFCC and their first and second derivatives. Experimental results showed that emotion recognizer using MFCC and their derivatives as a feature showed better performance than that using the Pitch and energy Parameters. For pattern recognition algorithm, GMM based emotion recognizer was superior to KNN and VQ based recognizer