• Journal of Biosystems Engineering
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• v.34 no.6
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• pp.454-461
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• 2009

The purpose of this study is to analyze the RFID recognition performance by level of water. A 13.56 MHz RFID management system for packaged liquid food logistics is consisted of antenna, reader, passive type tags, and embedded controller. The tests were conducted at different level of water, distances between tag and antenna, and position of attached tags. To analyze the RFID recognition performance, maximum recognition distances for a container and recognition rates for a logistics made of 27 containers were measured and analyzed. The maximum recognition distance for a container was different depending on position of attached tags, and attached tag at upside position showed a good performance. But, the recognition rate of 27 containers showed a good ability for attached tags at front side position, 30~35 cm distance to antenna, and water level 1. Therefore, to manage packaged liquid food logistics using RFID system, position of attached tag, distances between tag and antenna, and level of water should be considered.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.876-883
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• 2003

In this paper, we propose an algorithm for organ recognition in ultrasound images using log power spectrum. The main procedure of the algorithm consists of feature extraction and feature classification. In the feature extraction, as a translation invariant feature, log power spectrum is used for extracting the information on echo of the organs tissue from a preprocessed input image. In the feature classification, Mahalanobis distance is used as a measure of the similarity between the feature of an input image and the representative feature of each class. Experimental results for real ultrasound images show that the proposed algorithm yields the improvement of maximum 30% recognition rate than the recognition algorithm using power spectrum and Euclidean distance, and results in better recognition rate of 10-40% than the recognition algorithm using weighted quefrency complex cepstrum.

• Journal of the Korean Society of Safety
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• v.26 no.5
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• pp.17-22
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• 2011

This study proposes feature extraction method of pattern recognition by evaluation of weld defects in weld zone of titanium. For this purpose, analysis objectives in this study are features of attractor quadrant and fractal dimension. Trajectory changes in the attractor indicated a substantial difference in fractal characteristics resulting from distance shifts such as porosity of weld zone. These differences in characteristics of weld defects enables the evaluation of unique characteristics of defects in the weld zone. In quantitative fractal feature extraction, feature values of 0.87 and 1.00 in the case of part of 0.5 skip distance and 0.72 and 0.93 in the case of part of 1.0 skip distance were proposed on the basis of fractal dimensions. Attractor quadrant point, feature values of 1.322 and 1.172 in the case of ${\phi}1{\times}3mm$ porosity and 2.264 and 307 in the case of ${\phi}3{\times}3mm$ porosity were proposed on the basis of distribution value. The Proposed feature extraction of pattern recognition in this study can be used for safety evaluation of weld zone in titanium.

• Journal of IKEEE
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• v.25 no.4
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• pp.613-618
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• 2021

Facial expression recognition has long been established as a subject of continuous research in various fields. In this paper, the relationship between each landmark is analyzed using the features obtained by calculating the distance between the facial landmarks in the image, and five facial expressions are classified. We increased data and label reliability based on our labeling work with multiple observers. In addition, faces were recognized from the original data and landmark coordinates were extracted and used as features. A genetic algorithm was used to select features that are relatively more helpful for classification. We performed facial recognition classification and analysis with the method proposed in this paper, which shows the validity and effectiveness of the proposed method.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.271-274
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• 1998

Ultrasonic sensors are becoming indispensable components in every sector of automation equipments due to many advantages. But the main purposes of the noncontact sensing device are rather narrowly confined within object detection and distance measurement. To widen the realm of the applications to object recognition, ultrasonic sensors need to improve the recognition resolution to a certain amount. To resolve the problem of spatial resolution restriction, an increased number of the sensors in the forms of a linear array or 2-dimensional array of the sensor has been used. Also better resolution has been obtained by shifting the array in several steps using mechanical actuators. For an object recognition using ultrasonic sensors, measurements of distance, shift, oblique angle in certain ranges should be obtained. But a little attention has been paid to the measurement of angles. In this paper we propose a practical method for an object angular value detection in addition to distance measurement in ultrasonic sensor array system with little additional hardware burden. Using the established measurement look-up table for the variations of distance, shift, angle and transmitter voltages for each sensor characteristics, a set of different return echo signals for adjacent receivers are processed to provide enhanced angular value reading for an object.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.251-256
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• 2019

This paper presents an algorithm for recognizing and tracking a vehicle at a distance using a monocular camera installed at the center of the windshield of a vehicle to operate an autonomous vehicle in a racing. The vehicle is detected using the Haar feature, and the size and position of the vehicle are determined by detecting the shadows at the bottom of the vehicle. The region around the recognized vehicle is determined as ROI (Region Of Interest) and the vehicle shadow within the ROI is found and tracked in the next frame. Then the position, relative speed and direction of the vehicle are predicted. Experimental results show that the vehicle is recognized with a recognition rate of over 90% at a distance of more than 100 meters.

• Smart Media Journal
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• v.11 no.10
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• pp.22-29
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• 2022

Voice interactions are particularly effective in applications targeting the digital underprivileged who are not proficient in the use of smart devices. However, applications based on open APIs are using voice signals only for short, fragmentary input and output due to the limitations of existing touchscreen-oriented UI and API provided. In this paper, we design a conversational voice interaction model for interactions between users and intelligent mobile/IoT applications and propose a keyword detection algorithm based on the edit distance. The proposed model and scheme were implemented in an Android environment, and the edit distance-based keyword detection algorithm showed a higher recognition rate than the existing algorithm for keywords that were incorrectly recognized through speech recognition.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.103-111
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• 2002

In this study, the natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.628-631
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• 1996

This paper proposes a surface recognition algorithm which determines the types of contact surfaces by fusing the information collected by the multisensor system, consisted of the optical tactile and force/torque sensors. Since the image shape measured by the optical tactile sensor system, which is used for determining the surface type, varies depending on the forces provided at the measuring moment, the force information measured by the f/t sensor takes an important role. In this paper, an image contour is represented by the long and short axes and they are fuzzified individually by the membership function formulated by observing the variation of the lengths of the long and short axes depending on the provided force. The fuzzified values of the long and short axes are fused using the average Minkowski's distance. Compared to the case where only the contour information is used, the proposed algorithm has shown about 14% of enhancement in the recognition ratio. Especially, when imposing the optimal force determined by the experiments, the recognition ratio has been measured over 91%.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.304-309
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• 2003

In this study, natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. Feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.