• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.776-788
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• 2020

In this paper, a vehicle type recognition system using deep learning and a license plate recognition system are proposed. In the existing system, the number plate area extraction through image processing and the character recognition method using DNN were used. These systems have the problem of declining recognition rates as the environment changes. Therefore, the proposed system used the one-stage object detection method YOLO v3, focusing on real-time detection and decreasing accuracy due to environmental changes, enabling real-time vehicle type and license plate character recognition with one RGB camera. Training data consists of actual data for vehicle type recognition and license plate area detection, and synthetic data for license plate character recognition. The accuracy of each module was 96.39% for detection of car model, 99.94% for detection of license plates, and 79.06% for recognition of license plates. In addition, accuracy was measured using YOLO v3 tiny, a lightweight network of YOLO v3.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.10
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• pp.1601-1610
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• 2009

Unplanned purchase is an unexpected buying behavior affected by product or marketing stimuli. Unplanned purchase does not follow the order of the rational decision making process. Through an in-depth interview, this study classified the types of unplanned purchase of clothing and examined the decision-making processes. The results (according to the need recognition level of consumers prior to stimuli) show three types of unplanned purchase of clothing products that are classified as: the need-manifesting type, the need-embodying type, and the need-reminding type. In addition, each type is reclassified into the high-cognition type and the low-cognition type according to the cognitive effort level of consumers during the purchase decision-making process. The need-manifesting type recognized a buying need after exposure to stimuli and then engaged in unplanned purchases. The need-embodying type recognized a problem, but the purchase intention was not concrete. The need-reminding type recognized a desire to buy clothing products, but temporarily forgot it, and then later remembered the problem recognition from the past after experiencing the stimuli.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.311-321
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• 2020

The purpose of this study was to analyze the recognition of secondary pre-physical education teachers' recognition for the learning athletics using Q methodology. P-sample was composed of 28 pre-secondary P·E teachers. The selected Q samples were arranged in the normal distribution form. The collected data were analyzed by factor analysis through varimax rotation using QUANL PC program. This study found four types of recognition on learning athletics. Type I is defined 'the type of recognition for education value.' Type II is defined 'the type of emphasizing assistant activities.' Type III is defined 'the type of an appeal difficulty to learn athletics skill.' Type IV is defined 'the type of emphasizing the basic movement value.' Based of the results of this study, the implications and direction to future research on athletics activities are suggested.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.411-425
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• 2021

In this paper, a vehicle recognition algorithm based on deep convolutional neural network and compression dictionary is proposed. Firstly, the network structure of fine vehicle recognition based on convolutional neural network is introduced. Then, a vehicle recognition system based on multi-scale pyramid convolutional neural network is constructed. The contribution of different networks to the recognition results is adjusted by the adaptive fusion method that adjusts the network according to the recognition accuracy of a single network. The proportion of output in the network output of the entire multiscale network. Then, the compressed dictionary learning and the data dimension reduction are carried out using the effective block structure method combined with very sparse random projection matrix, which solves the computational complexity caused by high-dimensional features and shortens the dictionary learning time. Finally, the sparse representation classification method is used to realize vehicle type recognition. The experimental results show that the detection effect of the proposed algorithm is stable in sunny, cloudy and rainy weather, and it has strong adaptability to typical application scenarios such as occlusion and blurring, with an average recognition rate of more than 95%.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.5
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• pp.266-279
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• 2003

In this paper, we propose machine printed character recognition methods which utilize the character type information and divide the character clusters. The characters are subdivided into a total of seven types, of which six types are for Hangul according to the grapheme combination fashions and one type for English characters, numerals, and symbols. According to the character type, we separate input character image into several recognition units and recognize them by using the direction angle feature. The recognition for each character type is completed by combining recognition units which are recognized by neural networks respectively For combining a total of seven character recognizers, we implemented seven methods such as switching method, integrating method, and their several variants. As experimental results, we obtained 98.2% recognition rate of simple switching method, 90.54% of integrating one, and between 97.35% and 98.65% of five variants.

• Design & Manufacturing
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• v.6 no.2
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• pp.59-63
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• 2012

In various industries, tactile recognition has been one of the important ways in displaying information because peoples like to touch and feel. Especially, how much the tactile information is efficiently recognizable is crucial for visually impaired persons in their daily lifes. However, existing design guidelines are insufficient to lead good tactile recognition. In this study, an experiment was performed to investigate proper tactile shapes (relievo / intaglio vs. filled / unfilled), sizes and depths for efficient tactile recognition. Moreover, this study scrutinized whether the recognition speed or error was varied depending on the type of displayed symbols (open vs. closed types) in tactile. The experimental results revealed that the 'relieve-filled' shape type was more rapidly recognizable than the other shapes, and the 'closed' type symbols (e.g., ${\square }$. ${\bigcirc}$) were more robustly recognizable than the 'open' type symbols (e.g, +, ^). Several design guidelines were presented based on the results. These guidelines can be applied to the design of tactile buttons in the devices that users should control them without visual attention, such as car steering wheels or MP3 players.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.77-82
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• 2017

In this paper, a new security algorithm to recognize the type of the vehicle with the vehicle image as a input image is suggested. The vehicle recognition security algorithm is composed of five core parts, such as the input image, background removal, edge areas extraction, pre-processing(binarization), and the vehicle recognition. Therefore, the final recognition rate of the security algorithm for vehicle type recognition can be affected by the function and efficiency of each step. After inputting image into a gray scale image and removing backgrounds, the binarization is performed by extracting only the edge region. After the pre-treatment process for making outlines clear, the type of vehicles is categorized into large vehicles, passenger cars and motorcycles through the ratio of height and width of the vehicle.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.28-36
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• 2018

There was a difference in recognition of respirators according to the educational performance environment. they were showed higher recognition of respirators of group by internal and external mix trainer, less than 6 months, over 1hour, more than 5 times, variety of education. To identify the relationship between types of job classification(typical and atypical)and the levels of recognition of respirators, a total of 153 workers in a business workplace. mainly, typical workers showed higher recognition of respirators than atypical workers. Training of correct wearing showed high demands both typical and atypical workers. Descriptive statistics(SAS ver 9.2)was performed. the results of recognition of respirators were analyzed the mean and standard deviation by t-test, and anova, fit factor is used geometric means(geometric standard deviation), paired t-test, Wilcoxon analysis(P=0.05). Particulate filtering facepiece respirators (PFFR) is one of the most widely used items of personal protective equipments, and a tight fit of the respirators on the wearers is critical for the protection effectiveness. In order to effectively protect the workers through the respirators, it is important to find and evaluate the ways that can be readily applicable at the workplace to improve the fit of the respirators. This study was designed to evaluate effects of mask style (cup or foldable type) and donning training on fit factors (FF) of the respirators, since these are available at various workplace, especially at small business workplace. A total of 40 study subjects, comprised of employment type workers in metalworking industries, were enrolled in this study. The FF were quantitatively measured before and after training related to the proper donning and use of cup or foldable-type respirators. The pass/fail criterion of FF was set at 100. After the donning training for the cup-type mask, fit test were increased by 769%. but foldable-type mask was also increased after the donning training, the GM of FF for the foldable-type mask and it's increase rate were smaller as compared to the cup-type mask. Furthermore, the differences of the increase rates of the GM of FF in employment type of the subjects were not significantly for the foldable-type mask. These results imply that the raining on the donning and use of PFFR can enhance the protection effectiveness of cup or foldable-type mask, and that the training effects for the foldable-type mask is less significant than that for the cup-type mask. Therefore, it is recommended that the donning training and fit tests should be conducted before the use of the PFFR, and listening to workers opinion regularly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.423-426
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• 1995

An image processing algorithm is developed in order to recognize the type of cars, the position of a number plate and the characters on the plate. To recognize the type af cars, comparison of two images is used. One has a car image, the other is just a background image without car. After that recognition, a vertical line filter is used to find the location of the plate. Finally the similarity method is used to recognize the numbers on the plates.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.2
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• pp.103-110
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• 2004

This paper proposes a new method on the EMG AR(autoregressive) modeling in pattern recognition for various head motions. The proper electrode placement in applying AR or cepstral coefficients for EMG signature discrimination is investigated. EMG signals are measured for different 10 motions with two electrode arrangements simultaneously. Electrode pairs are located separately on dominant muscles(S-type arrangement), because the bandwidth of signals obtained from S-type placement is wider than that from C-type(closely in the region between muscles). From the result of EMG pattern recognition test, the proposed mIAR(modified integrated mean autoregressive model) technique improves the recognitions rate around 17-21％ compared with other the AR and cepstral methods.