• Journal of the Semiconductor & Display Technology
• /
• v.10 no.3
• /
• pp.53-59
• /
• 2011

This paper proposes a new method of traffic signal detection and recognition in an RGB color model. The proposed method firstly processes RGB-filtering in order to detect traffic signal candidates. Secondly, it performs adaptive threshold processing and then analyzes connected components of the binary image. The connected component of a traffic signal has to be satisfied with both a bounding box rate and an area rate that are defined in this paper. The traffic signal recognition system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.3
• /
• pp.97-107
• /
• 1998

In face recognition based on the Karhunen-Loeve approximation, amplitudespectra of Fourier transformed facial images were used. We found taht the use of amplitude spetra gives not only the shift-invariance property but also some improvment of recognition rate. This is because the distance between the varing faces of a person compared with that between the different persons perfomed computer experiments on face recognitio with varing facial images obtained from total 55 male and 25 females. We confirmed that the use of amplitude spectra of Fourier-trnsformed facial imagesgives better recognition rate for avariety of varying facial images including shifted ones than the use of direct facial images does.

• Journal of the Semiconductor & Display Technology
• /
• v.19 no.2
• /
• pp.100-104
• /
• 2020

Over the past several years, deep learning has been widely used for feature extraction in image and video for various applications such as object classification and facial recognition. This paper introduces an implantation of embedded Linux system for embossed digits recognition using CNN based deep learning methods. For this purpose, we implemented a coin recognition system based on deep learning with the Keras open source library on Raspberry PI. The performance evaluation has been made with the success rate of coin classification using the images captured with ultra-wide angle camera on Raspberry PI. The simulation result shows 98% of the success rate on average.

• Journal of Information Processing Systems
• /
• v.8 no.3
• /
• pp.445-458
• /
• 2012

Image feature extraction is one of the basic works for biometric analysis. This paper presents the novel concept of application of ridgelets for iris recognition systems. Ridgelet transforms are the combination of Radon transforms and Wavelet transforms. They are suitable for extracting the abundantly present textural data that is in an iris. The technique proposed here uses the ridgelets to form an iris signature and to represent the iris. This paper contributes towards creating an improved iris recognition system. There is a reduction in the feature vector size, which is 1X4 in size. The False Acceptance Rate (FAR) and False Rejection Rate (FRR) were also reduced and the accuracy increased. The proposed method also avoids the iris normalization process that is traditionally used in iris recognition systems. Experimental results indicate that the proposed method achieves an accuracy of 99.82%, 0.1309% FAR, and 0.0434% FRR.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.495-497
• /
• 1993

This paper presents spoken numbers recognition method using a spatio-temporal network This network is efficient in processing the spectrum sequences of speech patterns as spatio-temporal patterns. The number of windows and channels is experimentally determined. The recognition rate has been improved by experiments done on various parameters. The test data is collected form 10 numbers spoken by 2 male and female speakers. A recognition rate of 80% was obtained on a test set of 50 words.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.1
• /
• pp.143-147
• /
• 2012

The rapid growth of camera technology can provide various types of information which was not previously provided. Furthermore, IP camera which has rapid data transfer rate and high resolution particularly provide a lot of useful functions beyond the existing simple surveillance capabilities. We are developing Real-Time Face Recognition Access Control System based on the camera technology, and improvement of face detection and recognition algorithms are vitally needed to realize that system. In this paper, we proposes a method to improve the computing speed and detection rate by adding new features to the existing Viola-Jones detection algorithm.

• MALSORI
• /
• no.61
• /
• pp.113-123
• /
• 2007

The environmental differences between training and testing mode are generally considered to be the critical factor for the performance degradation in speaker recognition systems. Especially, general speaker recognition systems try to get as clean speech as possible to train the speaker model, but it's not true in real testing phase due to environmental and channel noise. So in this paper, the new method of weighting the frame-based likelihood according to frame SNR is proposed in order to cope with that problem. That is to make use of the deep correlation between speech SNR and speaker discrimination rate. To verify the usefulness of this proposed method, it is applied to the context dependent speaker identification system. And the experimental results with the cellular phone speech DB which is designed by ETRI for Koran speaker recognition show that the proposed method is effective and increase the identification accuracy by 11% at maximum.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.3
• /
• pp.132-140
• /
• 1994

SCRIPT (Symbol/Character Recognition In Pen-based Technology) is an algorithm for on-line recognition of handwriting Hangeul. English upperacase letters, decimal digits, and some keyboard symbols. The shape of handwriting symbols has a large variation even when written by the same person. Though the feature analysis approach using a conventional decision tree is efficient, it is not robust under shape variations and prone to misclassification. Thus, a new method to overcome this shortcoming is necessary. In this paper, a feature analysis algorithm using two fuzzy decision trees which utilize the hierarchical property of the pattern is proposed. The first tree is used to represent the stroke shape, and the other tree is used to represent the relation between the strokes. since this method stores various possibilities. it is robust to shape variations and can readily modify false selections. In addition, there is a large increase in the recognition rate of high-level patterns due to low-level candidated. Experimental results show 91% recognition rate for Hangeul at the recognition speed of 0.33 second per character, and the recognition rate of alphanumerics and some keyboard symbols is 95% at 0.08 second per symbol. This is 8~18% increase in the recognition rate over th method not applying fuzzy decision trees.

• Journal of Technologic Dentistry
• /
• v.32 no.3
• /
• pp.221-232
• /
• 2010

Purpose: It is necessary for dental technicians exposed to hazardous chemicals in the dental laboratories to be informed of the various harmful effects of chemicals for their health and safety. The purposes of this study was to investigate the actual condition of the use of MSDS in dental laboratories and the recognition rate of MSDS for dental technicians. Methods: 231 dental technicians who were self-written questionnaire. The results were analyzed by SPSS 12.0. The answers to the questionnaire underwent frequency analysis, chi-square test and correlation analysis were performed to investigate association between health effects and recognition rate of chemical information. Results: The results from the effects of damage caused by chemicals 60.7%, and when it was less than 2 years working experience 47.6%. Currently any dental laboratories(rooms) was not furnished MSDS(0%) and even similar data furnishing rate was only 17.3%. Answer rate of 'Do not know about MSDS' was 73.6%. In addition to, education in the types and characteristics of chemicals(74.5%) does not receive all the higher education. For the question of 'To prevent human risks and accidents, is to provide chemical information needed', the answer rate of 'needed' was 87.2%. Moreover, the answer rate of 'To provide chemical information that could prevent accidents' was 76.6%. Therefore it was found that dental technicians need to be provided for chemical information. In addition, they wanted to get education related to chemicals used in the workplace(80.5%), and 90.9% was answered that they was willing to keep MSDS in they workplace. Conclusion: This study investigated the current dental laboratories(rooms) and the MSDS for the awareness and recognition of workers was very low, education was not being conducted properly. The dental laboratories(rooms) of the compact characteristics of the MSDS was not reasonably accessible and the furnishing location, dental laboratories(rooms) for the real item was needed for improvement. MSDS for dental technicians through education and promotion of information about chemicals and chemicals was to prevent health problems caused by the MSDS that will raise awareness of the necessity.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.29 no.1
• /
• pp.69-81
• /
• 2019

Objective: The purpose of this study was to find out what kind of change in death rate when job stress is solved by calculating job stress relieve coefficient. Methods: This study used the data of the fourth working condition survey. Regression analysis was used to determine the relationship between health effects recognition and Death rate per 10,000 workers. After that the recognizing and non - recognizing groups were categorized by health effects recognition, and the differences between the two groups were confirmed by cross tabulation analysis. Results: Regress analysis P-value is 0.011 and $R^2$ is 0.979. Death rate per 10,000 worker increased with the increase in the number of non - health impact recognizing group. The relieve factors were (1) work culture(2.859) (2) physical environment(2.184), (3) improper reward (1,839), (4) relationship conflict(1.646), (5) job requirement(1.613), (6) job autonomy(1.354), (7) job instability(1.334), And (8) organizational system(1.201). The higher the relieve coefficient is, the higher the probability of belonging to the non - health impact recognizing group when there is no job stress factor. Conclusions: When job stress is resolved, there is a high probability that the health impact recognition is reduced, which can lead to an increase in death rate. but according to previous studies, Job stress can cause accidents by reducing the safety behavior of accidents. The job stress management plan should simultaneously consider reducing job stress and increasing health impact recognition.