• International journal of advanced smart convergence
• /
• 제9권1호
• /
• pp.113-120
• /
• 2020

Recently, the license plate OCR system has been commercialized in a variety of fields and preferred utilizing low-cost embedded systems using only cameras. This system has a high recognition rate of about 98% or more for the environments such as parking lots where non-vehicle is restricted; however, the environments where non-vehicle objects are not restricted, the recognition rate is about 50% to 70%. This low performance is due to the changes in the environment by non-vehicle objects in real-time situations that occur anomaly data which is similar to the license plates. In this paper, we implement the appropriate anomaly detection based on semi-supervised learning for the license plate OCR system in the real-time environment where the appearance of non-vehicle objects is not restricted. In the experiment, we compare systems which anomaly detection is not implemented in the preceding research with the proposed system in this paper. As a result, the systems which anomaly detection is not implemented had a recognition rate of 77%; however, the systems with the semi-supervised learning based on anomaly detection had 88% of recognition rate. Using the techniques of anomaly detection based on the semi-supervised learning was effective in detecting anomaly data and it was helpful to improve the recognition rate of real-time situations.

• 한국시뮬레이션학회논문지
• /
• 제18권2호
• /
• pp.9-17
• /
• 2009

얼굴인식이 널리 사용되기 시작하면서, 얼굴 데이터베이스는 많은 양의 얼굴정보를 담게 되었다. 이러한 얼굴 데이터의 증가로 인하여 분산처리 방법을 이용한 얼굴인식이 주요 주제로 대두되고 있다. 하지만 기존 방법에서는 대용량의 데이터를 전송하는 방법에 대한 논의가 부족하다. 이에 본 논문은 분산처리 환경에서 퍼지로직 기반 비트압축률 선택을 통한 얼굴인식을 제안한다. 제안한 방법은 얼굴인식률, 얼굴인식 수행시간, 전송된 비트 길이를 바탕으로 퍼지추론을 하여 효과적인 압축률을 선택한다. 우리는 제안한 방법과 압축을 하지 않은 데이터, 고정 압축률을 적용한 데이터에 따른 얼굴인식률과 얼굴인식 수행시간을 측정하여 비교하였다. 실험 결과는 퍼지로직 기반 압축률 선택이 수행시간을 감소시키면서도 합리적인 인식률을 유지하는 효과가 있음을 보여준다.

• 패션비즈니스
• /
• 제21권3호
• /
• pp.14-28
• /
• 2017

This purpose of this study to analyze effect material properties have on change in QR code recognition rate according to change of materials by comparing recognition rate of color QR code. QR code applied to textile materials has the advantage of being washable and being applicable to lost child prevention goods or clothes or a person with dementia through record of information relating to the material or input of additional information, differently from QR code printed on the conventional paper. An effective method of entering QR code in textile materials is Digital Textile Printing(DTP), that facilitates printing by rapidly applying diverse information, and small quantity production. It is possible to tailor various QR codes according to use. Regarding samples to use, cotton material used in clothing products and Tyvek material recently applied to clothing and related products were selected. Reactive dyes were used for cotton, pigment was used for Tyvek, and QR code was printed with an inkjet printer by direct printing method. Printing methods and surface textures are different between cotton and Tyvek. It was revealed that consequent print results and results of recognition rate were different. Regarding color to be printed, 2015 S/S - 2017 S/S color presented by Pantone was used. Color combination affected recognition rate of color QR code. Understanding color combination, material properties and print characteristics may be helpful in increasing recognition rate of color QR code, and may contribute to usability of color QR code applied to textile materials in the future.

• 패션비즈니스
• /
• 제20권4호
• /
• pp.50-71
• /
• 2016

This study analyzed the recognition rate of QR codes printed by digital transfer textile printing for mobile application. The purpose was to identify conditions that increase recognition rates of QR codes printed on textile, in order to increase utility of QR codes in the textile and fashion industries. The study focused on differences in the color of the QR codes and denier, which is a unit of textile fineness measurement, of the textile on which the QR codes were printed. And the recognition rates of QR codes according to the color and denier were analyzed. According to the result of this study, the colors of QR codes had an effect on the recognition of the codes by mobile applications. Specifically, strong contrast, i.e., bright background and relatively dark module, increased the recognition rate of the QR codes. Digital transfer textile printing tend to change the hue of red and yellow and increase brightness, and change in the printed colors also had an effect on the recognition rate of QR codes. There was a clear difference in the color and recognition rate of the printed QR code according to the denier of the textile, and this suggests denier has an effect on the recognition rate. The findings in this study can provide basic data for future research on QR codes digital printed on textile.

• 한국컴퓨터정보학회논문지
• /
• 제21권9호
• /
• pp.27-36
• /
• 2016

Recognition of grapheme is a very important process in the recognition within 'Hangul(Korean written language)' letters using phoneme recognition. It is because the success or failure in the recognition of phoneme greatly affects the recognition of letters. For this reason, it is reported that separation of phonemes is the biggest difficulty in the phoneme recognition study. The current study separates and suggests the new phonemes that used the connective elements that are helpful for dividing phonemes, recommends the features for recognition of such suggested phonemes, databases this, and carried out a set of experiments of recognizing phonemes using the suggested features. The current study used 350 letters in the experiment of phoneme separation and recognition. In this particular kind of letters, there were 1,125 phonemes suggested. In the phoneme separation experiment, the phonemes were divided in the rate of 100%, and the phoneme recognition experiment showed the recognition rate of 98% in recognizing only 14 phonemes into different ones.

• 음성과학
• /
• 제8권4호
• /
• pp.17-33
• /
• 2001

In this paper, we implement the large variable vocabulary speech recognition system, which is characterized by no additional pre-training process and no limitation of recognized word list. We have designed the system in order to achieve the high recognition rate using the decision tree based state tying algorithm and in order to reduce the processing time using the gaussian selection based variable flooring algorithm, the limitation algorithm of the number of nodes and ENNS algorithm. The gaussian selection based variable flooring algorithm shows that it can reduce the total processing time by more than half of the recognition time, but it brings about the reduction of recognition rate. In other words, there is a trade off between the recognition rate and the processing time. The limitation algorithm of the number of nodes shows the best performance when the number of gaussian mixtures is a three. Both of the off-line and on-line experiments show the same performance. In our experiments, there are some differences of the recognition rate and the average recognition time according to the distinction of genders, speakers, and the number of vocabulary.

• 말소리와 음성과학
• /
• 제9권4호
• /
• pp.43-50
• /
• 2017

These days voice models of speech recognition software are sophisticated enough to process the natural speech of people without any previous training. However, not much research has reported on the use of speech recognition tools in the field of pronunciation education. This paper examined Google speech recognition of a short English paragraph produced by Korean college students in clear and casual speech styles in order to diagnose and resolve students' pronunciation problems. Thirty three Korean college students participated in the recording of the English paragraph. The Google soundwriter was employed to collect data on the word recognition rates of the paragraph. Results showed that the total word recognition rate was 73% with a standard deviation of 11.5%. The word recognition rate of clear speech was around 77.3% while that of casual speech amounted to 68.7%. The reasons for the low recognition rate of casual speech were attributed to both individual pronunciation errors and the software itself as shown in its fricative recognition. Various distributions of unrecognized words were observed depending on each participant and proficiency groups. From the results, the author concludes that the speech recognition software is useful to diagnose each individual or group's pronunciation problems. Further studies on progressive improvements of learners' erroneous pronunciations would be desirable.

• ETRI Journal
• /
• 제46권1호
• /
• pp.22-34
• /
• 2024

Exposure to varied noisy environments impairs the recognition performance of artificial intelligence-based speech recognition technologies. Degraded-performance services can be utilized as limited systems that assure good performance in certain environments, but impair the general quality of speech recognition services. This study introduces an audiovisual speech recognition (AVSR) model robust to various noise settings, mimicking human dialogue recognition elements. The model converts word embeddings and log-Mel spectrograms into feature vectors for audio recognition. A dense spatial-temporal convolutional neural network model extracts features from log-Mel spectrograms, transformed for visual-based recognition. This approach exhibits improved aural and visual recognition capabilities. We assess the signal-to-noise ratio in nine synthesized noise environments, with the proposed model exhibiting lower average error rates. The error rate for the AVSR model using a three-feature multi-fusion method is 1.711%, compared to the general 3.939% rate. This model is applicable in noise-affected environments owing to its enhanced stability and recognition rate.

• Journal of International Society for Simulation Surgery
• /
• 제2권2호
• /
• pp.64-66
• /
• 2015

Purpose : In this paper we proposed cascade feature filter and projection method for rapid human face recognition for the large-scale high-dimensional face database. Materials and Methods : The relevant features are selected from the large feature set using Fast Correlation-Based Filter method. After feature selection, project them into discriminant using Principal Component Analysis or Linear Discriminant Analysis. Their cascade method reduces the time-complexity without significant degradation of the performance. Results : In our experiments, the ORL database and the extended Yale face database b were used for evaluation. On the ORL database, the processing time was approximately 30-times faster than typical approach with recognition rate 94.22% and on the extended Yale face database b, the processing time was approximately 300-times faster than typical approach with recognition rate 98.74 %. Conclusion : The recognition rate and time-complexity of the proposed method is suitable for real-time face recognition system on the large-scale high-dimensional face database.

• ETRI Journal
• /
• 제36권6호
• /
• pp.1016-1022
• /
• 2014

This paper presents a hybrid model solution for user motion recognition. The use of a single classifier in motion recognition models does not guarantee a high recognition rate. To enhance the motion recognition rate, a hybrid model consisting of decision trees and artificial neural networks is proposed. We define six user motions commonly performed in an indoor environment. To demonstrate the performance of the proposed model, we conduct a real field test with ten subjects (five males and five females). Experimental results show that the proposed model provides a more accurate recognition rate compared to that of other single classifiers.