• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.817-828
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• 2004

In this paper, we propose vector-based face generation system that uses montage and shading method and preserves designer(artist)'s style. Proposed system generates character's face similar to human face automatically using facial features that extracted from a photograph. In addition, unlike previous face generation system that uses contours, we propose the system is based on color and composes face from facial features and shade extracted from a photograph. Thus, it has advantages that can make more realistic face similar to human face. Since this system is vector-based, the generated character's face has no size limit and constraint. Therefore it is available to transform the shape freely and to apply various facial expressions to 2D face. Moreover, it has distinctiveness with another approaches in point that can keep artist's impression just as it is in result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1338-1344
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• 2010

A person does communication between each other using language. But In the case of disabled person can not communication own idea to use writing and gesture. Therefore, In this paper, we embodied communication system using the facial muscle signals so that disabled person can do communication. Especially, After feature extraction of the EEG included facial muscle, it is converted the facial muscle into control signal, and then select character and communication using a minimum list keyboard.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1256-1259
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• 2002

In this paper, we have proposed license plate recognition system for multi-national vehicle license plate using geometric features along with hybrid and seven segment pattern vectors. In the proposed system, we suggested to find horizontal and vertical relation after going through preparation process with inputted real-time license plate image of Korea and Japan, and then to classify license plate with using characteristic and geometric information of license plates. It classifies the extracted license plate images into letters and numbers, such as local name, local number, classification character and license consecutive numbers, and recognize license plate of Korea and Japan by applying hybrid and seven segments pattern vectors to classified letter and number region. License plate extraction step of the proposed system uses width and length information along with relative rate of Korean and Japanese license plate. Moreover, it exactly segmentation by letters with using each letter and number position information within license plate region, and recognizes Korean and Japanese license plates by applying hybrid and seven segment pattern vectors, containing characteristics related to letter size and movement within segmented letter area. As the result of testing the proposed system in real experiment, it recognized regardless of external lighting conditions as well as classifying license plates by nations, Korea and Japan. We have developed a system, recognizing regardless of inputted structural character of vehicle licenses and external environment.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.51-60
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• 2020

Optical character recognition (OCR) has been studied for decades because it is very useful in a variety of places. Nowadays, OCR's performance has improved significantly due to outstanding deep learning technology. Thus, there is an increasing demand for commercial-grade but affordable OCR systems. We have developed a low-cost, high-performance OCR system for the industry with the cheapest embedded developer kit that supports GPU acceleration. To achieve high accuracy for industrial use on limited computing resources, we chose a state-of-the-art text recognition algorithm that uses an end-to-end deep learning network as a baseline model. The model was then improved by replacing the feature extraction network with the best one suited to our conditions. Among the various candidate networks, EfficientNet-B3 has shown the best performance: excellent recognition accuracy with relatively low memory consumption. Besides, we have optimized the model written in TensorFlow's Python API using TensorFlow-TensorRT integration and TensorFlow's C++ API, respectively.

• Journal of IKEEE
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• v.24 no.4
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• pp.1086-1092
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• 2020

An autonomous agent for real world should be able to recognize text in scenes. With the advancement of deep learning, various DNN models have been utilized for transformation, feature extraction, and predictions. However, the existing state-of-the art STR (Scene Text Recognition) engines do not achieve the performance required for real world applications. In this paper, we introduce a performance-improvement method through an add-on composed of an OCR (Optical Character Recognition) engine and a classifier for STR engines. On instances from IC13 and IC15 datasets which a STR engine failed to recognize, our method recognizes 10.92% of unrecognized characters.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.528-538
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• 2003

A SCCRS (Speech and Character Combined Recognition System) is developed for working on mobile devices such as PDA (Personal Digital Assistants). In SCCRS, the feature extraction is separately carried out for speech and for hand-written character, but the recognition is performed in a common engine. The recognition engine employs essentially CHMM (Continuous Hidden Markov Model), which consists of variable parameter topology in order to minimize the number of model parameters and to reduce recognition time. For generating contort independent variable parameter model, we propose the SSMS(Successive State and Mixture Splitting), which gives appropriate numbers of mixture and of states through splitting in mixture domain and in time domain. The recognition results show that the proposed SSMS method can reduce the total number of GOPDD (Gaussian Output Probability Density Distribution) up to 40.0% compared to the conventional method with fixed parameter model, at the same recognition performance in speech recognition system.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.357-364
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• 2005

In this paper, we propose an accurate and fast keyword spotting system for searching user-specified keyword in Hangul document images by using two-level image-to-image matching. The system is composed of character segmentation, creating a query image, feature extraction, and matching procedure. Two different feature vectors are used in the matching procedure. An experiment using 1600 Hangul word images from 8 document images, downloaded from the website of Korea Information Science Society, demonstrates that the proposed system is superior to conventional image-based document retrieval systems.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.257-266
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• 2004

This paper proposes caricature generation system that uses shading mechanism that extracts textural features of face. Using this method, we can get more realistic caricature. Since this system If vector-based, the generated character's face has no size limit and constraint. so it is available to transform the shape freely and to apply various facial expressions to 2D face. Moreover, owing to the vector file's advantage, It can be used in mobile environment as small file size This paper presents methods that generate vector-based face, create shade and synthesize the shade with the vector face.

• Journal of the Korean Society of Industry Convergence
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• v.3 no.3
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• pp.229-236
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• 2000

This paper proposes on the Hanguel character CAI system using image processing. For this, firstly, the characters written by elementary school students or foreigners arc captured by CCD camera. Secondly, Recognition is accomplished by pre-processing, thinning and recognition processes. Thirdly, strokes are separated and beauty evaluation is done by matching feature value of the input image from the similarity measure function. In particular, this paper describe to define the similarity measuring function using extracted factor values after getting the beauty evaluation factor values of the consonant in the entire CAI system. Finally, the effectiveness of the proposed system is demonstrated by experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.113-116
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• 2003

A person does communication between each other using language. But, In the case of disabled person, call not communicate own idea to use writing and gesture. We embodied communication system using the ERG so that disabled Person can do communication. After feature extraction of the EEG included facial muscle, it is converted the facial muscle into control signal. and then did so that can select character and communicate idea.