• The Journal of the Acoustical Society of Korea
• /
• v.18 no.1E
• /
• pp.27-31
• /
• 1999

Recent linguistic researches have brought into focus the relations between prosodic structures and syntactic, semantic or phonological structures. Most of them prove that prosodic information is available for understanding syntactic, semantic and discourse structures. But this result has not been integrated yet into recent Korean speech recognition or understanding systems. This study, as a part of integrating prosodic information into the speech recognition system, proposes an automatic detection technique of Korean accentual phrase boundaries by using one-stage DP, and the normalized pitch pattern. For making the normalized pitch pattern, this study proposes a method of modified normalization for Korean spoken language. For the experiment, this study employs 192 sentential speech data of 12 men's voice spoken in standard Korean, in which 720 accentual phrases are included, and 74.4% of the accentual phrase boundaries are correctly detected while 14.7% are the false detection rate.

• Journal of Korea Multimedia Society
• /
• v.14 no.8
• /
• pp.992-999
• /
• 2011

This paper proposed a human body posture recognition program based on haar-like feature and hand activity detection. Its distinguishing features are the combination of face detection and motion detection. Firstly, the program uses the haar-like feature face detection to receive the location of human face. The haar-like feature is provided with the advantages of speed. It means the less amount of calculation the haar-like feature can exclude a large number of interference, and it can discriminate human face more accurately, and achieve the face position. Then the program uses the frame subtraction to achieve the position of human body motion. This method is provided with good performance of the motion detection. Afterwards, the program recognises the human body motion by calculating the relationship of the face position with the position of human body motion contour. By the test, we know that the recognition rate of this algorithm is more than 92%. The results show that, this algorithm can achieve the result quickly, and guarantee the exactitude of the result.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.05a
• /
• pp.521-524
• /
• 2013

In this paper, the algorithm that recognizes the gesture by configuring the feature information obtained through Improved Higher Order Local Correlation Features as low dimensional gesture symbol was described. Since the proposed method doesn't require a lot of computations compared to the existing geometric feature based method or appearance based methods and it can maintain high recognition rate by using the minimum information, it is very well suited for real-time system establishment.

• Journal of Information Processing Systems
• /
• v.12 no.4
• /
• pp.591-611
• /
• 2016

High dimensional space is the biggest problem when classification process is carried out, because it takes longer time for computation, so that the costs involved are also expensive. In this research, the facial space generated from homogeneous and non-homogeneous polynomial was proposed to extract the facial image features. The homogeneous and non-homogeneous polynomial-based eigenspaces are the second opinion of the feature extraction of an appearance method to solve non-linear features. The kernel trick has been used to complete the matrix computation on the homogeneous and non-homogeneous polynomial. The weight and projection of the new feature space of the proposed method have been evaluated by using the three face image databases, i.e., the YALE, the ORL, and the UoB. The experimental results have produced the highest recognition rate 94.44%, 97.5%, and 94% for the YALE, ORL, and UoB, respectively. The results explain that the proposed method has produced the higher recognition than the other methods, such as the Eigenface, Fisherface, Laplacianfaces, and O-Laplacianfaces.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.55 no.2
• /
• pp.75-81
• /
• 2006

The purpose of this paper is to recognize the feature points of ECG and human pulse -which signal shows the electric and physical characteristics of heart respectively- using wavelet transform. Wavelet transform is proper method to analyze a signal in time-frequency domain. In the process of wavelet decomposition and reconstruction of ECG and human pulse signal, we removed the noises of signal and recognized the feature points of signal using some of decomposed component of signal. We obtained the result of recognition rate that is estimated about 95.45$\%$ in case of QRS complex, 98.08$\%$ in case of S point and P point and 92.81$\%$ in case of C point. And we computed diagnosis parameters such as RRI, U-time and E-time.

• Journal of the Institute of Convergence Signal Processing
• /
• v.14 no.1
• /
• pp.21-26
• /
• 2013

The objective of this study was to develop a system for handwriting recognition in three dimensions (3D) to authenticate users. While previous studies have used a stylus pen for two-dimensional input on a tablet, this study uses the Wii Remote controller because it can capture 3D human motion and could therefore be more effective means of recognition. The information obtained from a Wii Remote controller included x and y coordinates, acceleration (x, y, z), angular velocity (pitch, yaw, roll), twelve input buttons, and time. The proposed system calculates distances using six features extracted after preprocessing the data. In an experiment where 15 subjects wrote "AIZU" 10 times, we obtained a 94.8% identification rate using a combination of writing velocity, the peak value of pitch, and the peak value of yaw. This suggests that this system holds promise for handwriting-based authentication in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.9
• /
• pp.2424-2441
• /
• 2012

In this paper, we propose a fake iris detection method that combines the optical and textural features of the human eye. To extract the optical features, we used dual Purkinje images that were generated on the anterior cornea and the posterior lens surfaces based on an analytic model of the human eye's optical structure. To extract the textural features, we measured the amount of change in a given iris pattern (based on wavelet decomposition) with regard to the direction of illumination. This method performs the following two procedures over previous researches. First, in order to obtain the optical and textural features simultaneously, we used five illuminators. Second, in order to improve fake iris detection performance, we used a SVM (Support Vector Machine) to combine the optical and textural features. Through combining the features, problems of single feature based previous works could be solved. Experimental results showed that the EER (Equal Error Rate) was 0.133%.

• The Science & Technology
• /
• v.11 no.9 s.112
• /
• pp.41-49
• /
• 1978

Automatic pattern recognition using computers has manu potential applications. In many cases successful automatic pattern recognition procedures require an analysis of texture of a picture by a conventional digital computer: but this involves a type af computing that is at the present time extremely time-consuming and thus very expensive. In response to this situation, TEXAC was designed and built which is capable of most whole picture operations at a rapid television rate of 1/30th of a second. The results of operations are displayed continuously on color and black-and-white television monitors. The paper presents the architecture of the TEXAC, the picture processing language developed and some of the results of TEXAC whole picture operations.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.22 no.5
• /
• pp.1-9
• /
• 1985

In this paper, a new methods which decomposes the handwritten-Hangout shape panerns into subpatterns and recognizes the decomposed subpatterns are proposed. the feature vcfices arc detected by searching boundary of the shape pattern and a topolo-gical structure is represented by a bridge links and contact links between the feature vertices. From the tpcological structure, Hangout shape patterns are decomposed into the subpatterns of 44-Korean alphabet. The 학obol and the local attributes are extracted from the subpattrrns and the subpatterns are recognized by matching those attributes with the dictionary. It is assured that this method is more effect and reasonable for deformed handwrioen Hangout shape patterns. Experimental results show that recognition rate is 99(%) and recogni-tion time is also reduced as those using the thinning process.

• International Journal of Reliability and Applications
• /
• v.10 no.1
• /
• pp.1-15
• /
• 2009

Even though the impact of manufacturing quality to reliability is not considered much as well as that of design area, a major cause of an early failure of the product is known as manufacturing problem. This research applies two different types of neural network algorithms, the Back propagation (BP) algorithm and Learning Vector Quantization (LVQ) algorithm, to identify and classify the nonrandom variation pattern on the control chart based on knowledge-based diagnosis of dimensional variation. The performance and efficiency of both algorithms are evaluated to choose the better pattern recognition system for auto body assembly process. To analyze hundred percent of the data obtained by Optical Coordinate Measurement Machine (OCMM), this research considers an application in which individual observations rather than subsample means are used. A case study for analysis of OCMM data in underbody assembly process is presented to demonstrate the proposed knowledge-based pattern recognition system.