• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.12
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• pp.1437-1450
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• 1992

This paper describes the feature extraction of the interdigital regions of palm, and proposes a personal verification algorithm using the extracted features and the pattern types of those. The procedures of the feature extraction are as follows : first, the interdigital region is partitioned into several subregions, examining the phase of rigdes in each subregion, deciding the direction of that phase, and making the direction matrix of the region, we analyze this direction matrix to contain a feature pattern, and then, yield the first core. Second, applying the thinning to around the first core and tracing the thinned ridges, we yield the feature pattern types and second cores. Finally, the feature patterns coordinates included all of them are built. Then, distances and directions from each second core reaching to all the others are yielded from that coordinates. These informations are used to make a feature parameter. In our verification algorithm, such pattern types, the numbers of feature patterns, theses positions and feature parameters are used to analyze.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.5
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• pp.470-475
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• 2009

This paper is the study which is head tracker using pattern matching. Proposal algorithm obtains initial attitude of head tracker using pattern matching. Optical head tracker consists of infrared LEDs(features) which are attached helmet as pattern, stereo infrared cameras. Proposal algorithm analyzes patterns by error rate of feature distance and estimates feature characteristic number. Initial attitude of head tracker is obtained to compare map data and feature characteristic number.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.842-847
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• 2005

This paper proposes a novel real-time EMG pattern recognition for the control of a multifunction myoelectric hand from four channel EMG signals. To cope with the nonstationary signal property of the EMG, features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a linear-nonlinear feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. We implement a real-time control system for a multifunction virtual hand. From experimental results, we show that all processes, including virtual hand control, are completed within 125 msec, and the proposed method is applicable to real-time myoelectric hand control without an operation time delay.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.54-59
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• 2004

We suggest a 3D vision inspection algorithm which is based on the external shape feature. Because many electronic parts have the regular shape, if we have the database of pattern and can recognize the object using the database of the object s pattern, we can inspect many types of electronic parts. Our proposed algorithm uses the geometrical pattern matching method and 3D database on the electronic parts. We applied our suggested algorithm fer inspecting several objects including typical IC and capacitor. Through the experiments, we could find that our suggested algorithm is more effective and more robust to the inspection environment(rotation angle, light source, etc.) than conventional 2D inspection methods. We also compared our suggested algorithm with the feature space trajectory method.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.167-174
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• 1998

The ultrasonic test is recognized for its significance as a non-destructive testing method to detect volume defects such as porosity and incomplete penetration which reduce strength in the weld zone. This paper illustrates the defect detection in the weld zone of ferritic carbon steel using ultrasonic wave and the evaluation of pattern recognition by chaotic feature extraction using time series signal of detected defects as data. Shown in the time series data were that the time delay was 4 and the embedding dimension was 6 which indicate the geometric dimension of the subject system and the extent of information correlation. Based on fractal dimension and lyapunov exponent in quantitative chaotic feature extraction, feature value of 2.15, 0.47 is presented for porosity and 2.24, 0.51 for incomplete penetration The precision rate of the pattern recognition is enhanced with these values on the total waveform of defect signal in the weld zone. Therefore, we think that the ultrasonic pattern recognition method of weld zone defects of ferritic carbon steel by ultrasonic-chaotic feature extraction proposed in this paper can boost precision rate further than the existing method applying only partial waveform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1253-1272
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• 2010

In this paper, we propose a new affine shape adaptation scheme for the affine invariant feature detector, in which the convergence stability is still an opening problem. This paper examines the relation between the integration scale matrix of next iteration and the current second moment matrix and finds that the convergence stability of the method can be improved by adjusting the relation between the two matrices instead of keeping them always proportional as proposed by previous methods. By estimating and updating the shape of the integration kernel and differentiation kernel in each iteration based on the anisotropy of the current second moment matrix, we propose a coarse-to-fine affine shape adaptation scheme which is able to adjust the pace of convergence and enable the process to converge smoothly. The feature matching experiments demonstrate that the proposed approach obtains an improvement in convergence ratio and repeatability compared with the current schemes with relatively fixed integration kernel.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.357-364
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• 1997

The early detection of breast cancer is clearly a key ingredient for reducing breast cancer mortality. Microcalcification is the only visible feature of the DCIS's(ductal carcinoma in situ) which consist 15 ~ 20% of screening-detected breast cancer. Therefore, the analysis of the shapes and distributions of microcalcifications is very significant for the early detection. The automatic detection procedures have b(:on the concern of digital image processing for many years. We proposed here one efficient method which is essentially statistical pattern classification accelerated by one representative feature, correlation coefficient. We compared the results by this additional feature with results by a simple gray level thresholding. The average detection rate was increased from 48% by gray level feature only to 83% by the proposed method The performances were evaluated with TP rates and FP counts, and also with Bayes errors.

• Korean Journal of Optics and Photonics
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• v.8 no.5
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• pp.403-409
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• 1997

We proposed a system that can perform pattern recognition based on parrallel optical feature extraction and performed experiments on this. The feature to be extracted are both 6 simple line orientations and two eigenvectors of the covariance matrix of the patterns that cannot be distinguished with the line orientation features alone. Our system consists of a feature-extraction part and a pattern-recognition part. The former that extracts the features in parallel with the multiplexed Vander Lugt filters was implemented optically, while the latter that performs the pattern recognition by the use of the extracted features was implemented in a computer. In the pattern recognition part, two methods are tested;one is to use an artificial neural network, which is trained to recognize the features directly, the other is to count the numbers of specific features simply and then to compare them with the stored reference feature numbers. We report the preliminary experimental results tested for 15 alpabet patterns with only straight line segments.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.52 no.2
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• pp.103-110
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• 2016

This study aims to estimate the species, size and shape of fish using a non-contact 3 dimensional pattern laser so that this preliminary test was carried out to understand the structural feature and length of goldfish according to water turbidity and depth in the aquacultural tank. 3-D pattern laser could clearly detect its morphological shape except the caudal fin due to soft tissue. Since the sensing strength of line laser light according to depth has sufficient power, it is possible to measure its depth and structural feature in the detected range. The result showed that the measured error of individual's fork length was less than ${\pm}1%$ in the water using 3-D pattern laser, when compared with the measured value in the air.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.4
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• pp.120-126
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• 1989

IC chip layout pattern recognition algorithms using image processing techniques are being developed for the automation of manufacturing and inspecting chips. Recognitioin of chip pattern requires feature extraction from nach rrame of chip image adn needs to match the feature data through all frames. In this paper, vertex position and form having layout information are extracted by the feature straightening algorithm, and global coordinates of layout pattern are extracted by the feature straightening algorithm, and global coordinates of layout pattern are obtainnd by vertex form matching from the overlapped area of neighbour frame.