• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.365-365
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• 2000

In this paper, we describe the system to recognize the six digit postal number of mails using neural network. Our zip-code recognition system consists of a preprocessing procedure for the original captured image, a segmentation procedure for separating an address block area with a shape, and recognition procedure for the cognition of a postal number. we extract the feature vectors that are the input of a neural network for the recognition process based on an area optimizing and an image thinning processing. The neural network classifies the zip-code in the mail and the recognized zip-code is verified through the zip-code database.

• Journal of IKEEE
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• v.21 no.2
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• pp.142-145
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• 2017

Currently, a trend in image processing is high-quality and high-resolution. The size and amount of image data are increasing exponentially because of the development of information and communication technology. Thus, license plate recognition with a single processor cannot handle the increasing data. This paper proposes a number plate recognition system using a distributed processing framework, Hadoop. Using SequenceFile format in Hadoop, each mapper performs a license plate recognition with a number of image data in a data block Experimental results show that license plate recognition performance with 16 data nodes accomplishes speedup of maximum 14.7 times comparing with one data node. In large dataset, the recognition performance is robust even if the number of data nodes increases gradually.

• Journal of Korean Academy of Rural Health Nursing
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• v.15 no.2
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• pp.41-48
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• 2020

Purpose: This study was a descriptive study to identify the factors affecting the dementia prevention behavior of elders in rural communities. Methods: The participants in this study were 125 elders aged 60 or older who lived in Eup or Myeon areas of P city. For data analysis, SPSS/WIN 22.0 was used to perform descriptive statistics, t-test, ANOVA, Pearson correlation, and linear multiple regression and mediated effects. Results: Scores for dementia recognition, dementia attitude and dementia prevention behavior averaged 5.6±2.50 points in the 0~11 range, 38.8±4.59 in 14~56 and 20.2±3.59 in 10~30 respectively. Dementia recognition (a), dementia attitude (b), dementia prevention behavior (c) and the number of chronic diseases of the elders (d) were positively or negatively correlated with each other (rab=.29, p<.01; rbc=.26, p<.01; rac=.36, p<.01; rad=-.29, p<.01; rcd=.19, p<.05). Factors affecting dementia prevention behavior were dementia recognition, dementia attitude, and degree of dementia interest. When the number of chronic diseases affects dementia prevention behavior, dementia recognition has a mediating effect. Conclusion: In order to prevent dementia among elders in rural areas, appropriate management of chronic diseases and provision of appropriate dementia-related education and information to enhance dementia recognition should be provided.

• Journal of the East Asian Society of Dietary Life
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• v.16 no.5
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• pp.497-505
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• 2006

This questionnaire study was conducted to investigate the levels of recognition and attitude for Korean traditional food among Japanese tourists. The aim was to provide basic data for making a detailed marketing direction alignment of globalization and commercialization of Korean traditional food. The results can be summarized as follows. The 'Korean wave(Hanliu)' was 'the number of known Korean star performers'(3.77 points), 'the number of watched Korean dramas'(3.67 points), 'the number of watched Korean movies'(3.44 points), 'the number of owned Korean singer's tapes or CDs'(3.04 points), 'the number of read books'(2.83 points), and 'the number of viewed cartoons'(2.49 points), in order. The high-intake frequency of Korean traditional foods was 'Bibimbap', 'Galbigui', 'Baechookimchi', 'Bulgogi', 'Kkakdugi', 'Tteokbokki', 'Japchae', 'Galbitang', 'fajeon', and 'Namullyu' in order. On the other hand, the intake frequency of 'Songpyeon', 'Inielmi', 'Sikhye' and 'Sujeonggwa' was very low. The most effective 'Hanliu' item for raising the recognition of Korean traditional food was 'the number of read books'. The most effective 'Hanliu' item for raising the experience of Korean cooking was 'the number of read books', followed by 'the number of watched Korean movies', 'the number of watched Korean dramas', and 'the number of viewed cartoons' in order. The most effective 'Hanliu' item for raising the intake frequency of Korean traditional food was' the number of watched Korean dramas', followed by 'the number of watched Korean movies' and 'the number of read books' in order.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.986-989
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• 2003

In the steel production line, the molten metal of a furnace is transformed into slab material and then move to the hot strip line, This paper describe about the real time recognition system of material management number, which is marked at the surface of a slab in the steel production line. This recognition processing should be performed before the slab is moved to the hot strip line. This system include following recognition steps. First, we remove noise from the captured slab image by use pre-filter. Second, we extract rough area, which is include slab number and then, we extract individual number area. Finally, we recognize material management number by use KLT(Karhunen-Loeve transform) algorithm. We applied our system to the real slave image, which was captured in the process line. In the results, we recognized slave number to the 94% accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.740-753
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• 2023

Text recognition in natural scene images is a challenging problem in computer vision. The accurate identification of ship number characters can effectively improve the level of ship traffic management. However, due to the blurring caused by motion and text occlusion, the accuracy of ship number recognition is difficult to meet the actual requirements. To solve these problems, this paper proposes a dual-branch network based on the CRNN identification network. The network couples image restoration and character recognition. The CycleGAN module is used for blur restoration branch, and the Pix2pix module is used for character occlusion branch. The two are coupled to reduce the impact of image blur and occlusion. Input the recovered image into the text recognition branch to improve the recognition accuracy. After a lot of experiments, the model is robust and easy to train. Experiments on CTW datasets and real ship maps illustrate that our method can get more accurate results.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.667-670
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• 1999

As the number of reference patterns increase in the text dependant speaker recognition, the recognition performance of the system degrades. So, if reference patterns were decreased the high recognition rate can be obtained. It’s because the speaker recognition can obtain the high discrimination. In this paper, to decrease the number of reference patterns, we choose candidate reference patterns to perform pattern matching with test pattern by high order component of the reflection coefficients of the uttered speech signal Consequently the total recognition rate of the proposed method is about 2% higher than that of the conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4098-4116
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• 2020

Mobile devices such as smartphones are very attractive targets for augmented reality (AR) services, but their limited resources make it difficult to increase the number of objects to be recognized. When the recognition process is scaled to a large number of objects, it typically requires significant computation time and memory. Therefore, most large-scale mobile AR systems rely on a server to outsource recognition process to a high-performance PC, but this limits the scenarios available in the AR services. As a part of realizing large-scale standalone mobile AR, this paper presents a solution to the problem of accuracy, memory, and speed for large-scale object recognition. To this end, we design our own basic feature and realize spatial locality, selective feature extraction, rough pose estimation, and selective feature matching. Experiments are performed to verify the appropriateness of the proposed method for realizing large-scale standalone mobile AR in terms of efficiency and accuracy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1105-1110
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• 2017

Speech with various emotions degrades the performance of the speaker recognition system. In this paper, a speaker recognition method using emotional adaptation has been proposed to improve the performance of speaker recognition system using affective speech. For emotional adaptation, emotional speaker model was generated from speaker model without emotion using a small number of training affective speech and speaker adaptation method. Since it is not easy to obtain a sufficient affective speech for training from a speaker, it is very practical to use a small number of affective speeches in a real situation. The proposed method was evaluated using a Korean database containing four emotions. Experimental results show that the proposed method has better performance than conventional methods in speaker verification and speaker recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.228-246
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• 2011

A 3D model based approach for a face representation and recognition algorithm has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper, we propose a novel 3D face representation algorithm based on a pixel to vertex map (PVM) to optimize the number of vertices. We explore shape and texture coefficient vectors of the 3D model by fitting it to an input face using inverse compositional image alignment (ICIA) to evaluate face recognition performance. Experimental results show that the proposed face representation and recognition algorithm is efficient in computation time while maintaining reasonable accuracy.