• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.85-90
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• 2012

Today many people are greatly interested in the environment. Especially increasing affluent of food causes a great amount of food waste. To handle this effectively, we now have a lot of problems of disposing garbage all over the world. In Korea, in order to reduce this garbage, we should use a standard plastic garbage bag in which we have to throw away our garbage. So it has an effect on significantly reducing the waste amount every year. Now, there are a lot of cases that residents use several times a standard plastic garbage bag. The purpose of this study is to develop the recognition device preventing the re-cycling of a standard plastic garbage bag. As a result, we obtain 1% error rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.87-95
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• 2006

In this paper, we propose a novel feature extraction method for face recognition, based on Discrete Cosine Transform (DCT), Energy Probability (EP), and Linear Discriminant Analysis (LDA). We define an energy probability as magnitude of effective information and it is used to create a frequency mask in OCT domain. The feature extraction method consists of three steps; i) the spatial domain of face images is transformed into the frequency domain called OCT domain; ii) energy property is applied on DCT domain that acquire from face image for the purpose of dimension reduction of data and optimization of valid information; iii) in order to obtain the most significant and invariant feature of face images, LDA is applied to the data extracted using frequency mask. In experiments, the recognition rate is 96.8% in ETRI database and 100% in ORL database. The proposed method has been shown improvements on the dimension reduction of feature space and the face recognition over the previously proposed methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.149-156
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• 2011

The purpose of this paper is the brief introduction of touchless fingerprint recognition and the assessment of interoperability between touchless and legacy rolled fingerprints for the wide use of touchless fingerprint recognition system. In order to assess the interoperability, the contrast and resolution of the touchless images are optimized firstly. And we perform the matching by using conventional minutiae-based matcher. Experimental results are promising that our touchless fingerprints have enough matching performance with equal error rate 7.9%. We can expect that our paper will make a significant contribution to the wide use of touchless fingerprint recognition and the increment of interoperability in the system integration between touchless-based and touch-based fingerprint systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.871-885
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• 2015

The improved DFSA for 2.4GHz multi-tags active RFID is suggested in 2 different ways: 1) simplified tag collection and Ack procedure using query command and 2) modified Schoute's method to control the number of slots in the frame. To evaluate the performance of the improved system we develop the simulation model. Varying the number of tags in the system we track the performance measures such as throughput, recognition time for multi-tags and tag recognition rate during a given time. The suggested method shows the best performance over all measures. Simplification of collection and Ack commands using query commands contributes to reducing tag recognition time. And the modified Schoute's method which controls the frame size using $k_1$ and $k_2$ contributes to throughput improvement and reduces target cognition time by reducing the number of collection rounds.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.505-511
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• 2005

Autonomic machines interacting with human should have capability to perceive the states of emotion and attitude through implicit messages for obtaining voluntary cooperation from their clients. Voice is the easiest and most natural way to exchange human messages. The automatic systems capable to understanding the states of emotion and attitude have utilized features based on pitch and energy of uttered sentences. Performance of the existing emotion recognition systems can be further improved withthe support of linguistic knowledge that specific tonal section in a sentence is related with the states of emotion and attitude. In this paper, we attempt to improve recognition rate of emotion by adopting such linguistic knowledge for Korean ending boundary tones into anautomatic system implemented using pitch-related features and multilayer perceptrons. From the results of an experiment over a Korean emotional speech database, the improvement of $4\%$ is confirmed.

• Journal of Digital Contents Society
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• v.12 no.3
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• pp.279-289
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• 2011

The latest hardware and software techniques are combined to give safe walking guidance and convenient service of realtime walking assistance system for visually impaired person. This system consists of obstacle detection and perception, place recognition, and sign recognition for pedestrian can safely walking to arrive at their destination. In this paper, we exploit the sign object detection system in subway station for sign recognition that one of the important factors of walking assistance system. This paper suggest the adaptive feature map that can be robustly extract the sign object region from complexed environment with light and noise. And recognize a sign using fast zernike moment features which is invariant under translation, rotation and scale of object during walking. We considered three types of signs as arrow, restroom, and exit number and perform the training and recognizing steps through adaboost classifier. The experimental results prove that our method can be suitable and stable for real-time system through yields on the average 87.16% stable detection rate and 20 frame/sec of operation time for three types of signs in 5000 images of sign database.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.239-249
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• 2020

In this study, 205 graduates of beauty majors were surveyed for the purpose of the study to analyze the differences between factors in each major by examining the impact of the perception of beauty education courses on site utilization, job utilization, and job satisfaction. The study found that practical skills were required as a supplemental major subject, and the theory

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.40-46
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• 2020

As interest in traffic safety increases, research on autonomous driving, which reduces the incidence of traffic accidents, is increased. Object recognition and detection are essential for autonomous driving. Therefore, research on object recognition and detection through traffic image big data is being actively conducted to determine the road conditions. However, because most existing studies use only daytime data, it is difficult to recognize objects on night roads. Particularly, in the case of a light source object, it is difficult to use the features of the daytime as it is due to light smudging and whitening. Therefore, this study proposes Yolo based light source object detection for traffic image big data processing. The proposed method performs image processing by applying color model transitions to night traffic image. The object group is determined by extracting the characteristics of the object through image processing. It is possible to increase the recognition rate of light source object detection on a night road through a deep learning model using candidate group data.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.303-304
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• 2007

In this paper, we implement an automatic distance speech recognition system for voiced-enabled services. We first construct a baseline automatic speech recognition (ASR) system, where acoustic models are trained from speech utterances spoken by using a cross-talking microphone. In order to improve the performance of the baseline ASR using distance speech, the acoustic models are adapted to adjust the spectral characteristics of speech according to different microphones and the environmental mismatches between cross-talking and distance speech. Next we develop a voice activity detection algorithm for distance speech. We compare the performance of the base-line system and the developed ASR system on a task of PBW (Phonetically Balanced Word) 452. As a result it is shown that the developed ASR system provides the average word error rate (WER) reduction of 30.6 % compared to the baseline ASR system.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.407-414
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• 2002

In this paper, we present a method that automatically generates concatenate morpheme based language models to improve the performance of Korean large vocabulary continuous speech recognition. The focus was brought into improvement against recognition errors of monosyllable morphemes that occupy 54% of the training text corpus and more frequently mis-recognized. Knowledge-based method using POS patterns has disadvantages such as the difficulty in making rules and producing many low frequency concatenate morphemes. Proposed method automatically selects morpheme-pairs from training text data based on measures such as frequency, mutual information, and unigram log likelihood. Experiment was performed using 7M-morpheme text corpus and 20K-morpheme lexicon. The frequency measure with constraint on the number of morphemes used for concatenation produces the best result of reducing monosyllables from 54% to 30%, bigram perplexity from 117.9 to 97.3. and MER from 21.3% to 17.6%.