• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.7-11
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• 2012

This paper develops the coin recognition and classification system using digital image processing technique. Coin images are taken by USB camera. The developed system can be used at home since it just needs USB camera and personal computers. For this development, some digital image prodessing technique is used; size recognition technique and color classification. Using Matlab, we design the graphic user interface and verify the reliability of the developed system with some simulation result.

• KIISE Transactions on Computing Practices
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• v.21 no.6
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• pp.424-429
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• 2015

This research proposes a new system for calculating the total amount of coins in an image. The proposed system identified and classified the coins in the image in realtime. The image was obtained using a USB camera. Most previous coin calculation systems only used size information. If the size of an object was incorrectly detected, it caused a misclassification. Especially, in case of the former 10 won, it had high error rate because it was similar in size to the 50 won and 100 won coin. The proposed system combines hue histogram information with size information to reduce errors in the classification process. When we only used size information in the classification experiment of 2,290 coins, the recognition rate was on average about 88.2%. When we combined hue information with size information the recognition rate increased to about 99.3%.

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

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.619-623
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• 1992

In pattern recognition, the conventional neural networks contain a large number of weights and require considerable training times and preprocessor to classify a transformed patterns. In this paper, we propose a constrained pattern recognition method which is insensitive to rotation of input pattern by various degrees and does not need any preprocessing. Because these neural networks can not be trained by the conventional training algorithm such as error back propagation, a novel training algorithm is suggested. As such a system is useful in problem related to calssify overse side and reverse side of 500 won coin. As an illustrative example, identification problem of overse and reverse side of 500 won coin is shown.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.29-32
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• 2001

In this paper, we applied the high-performance PGAP(Parallel Genetic Algorithm Processor) to recognizing rotated pattern. In order to perform this research efficiently, we used Multi-PGAP system consisted of four PGAP. In addition, we used mental rotation based on the rotated pattern recognition mechanism of human to reduce the number of operation. Also, we experimented with distinguishing specific pattern from similar coin patterns and determine rotated angle between patterns. The result showed that the development of future artificial recognition system is feasible by employing high performance PGAPS.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.141-157
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• 2023

The present work aimed to present the development of 'Funt', the augmented reality-based digital app as an educational tool for foreign language learning. Our work further evaluated the learning efficacy of the tool by the assessment of the three dependent measures including learning motivation, learning satisfaction, and learning involvement. With a learning app of 'Funt', students can use AR app to access recognition-based or location-based experiences such that any objects, artifacts, or media appear to be in the app. Students are then able to interact with the digital content by manipulating it to learn more about it. Students's engagement should also increase when they create their own experience in AR to demonstrate their understanding of a particular concept or words. Learning effects were evaluated on survey data collected from a hundred respondents aging six to nine years. One-group design for pre-test and post-test was utilized to examine the differences of learning efficacy by comparing the non-'Funt' group and the Funt group scores. A pairwise t-Test was performed for pairwise comparisons between two learning groups. The results indicate that the 'Funt' group scored significantly higher than the non-'Funt' group in the measures of learning motivation, learning satisfaction, and learning involvement. Overall, our results suggest that 'Funt' attracted the students' attention, provided them with a fun context to learn English vocabulary, and develop positive motivation and satisfaction towards vocabulary learning through AR technology.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2821-2823
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• 1999

In this paper we proposed an algorithm for rotation-invariant pattern recognition and rotated angle estimation between two patterns by employing selective template matching. Generally template matching has been used in determining the location of pattern but template matching requires a number of calculating correlation. To reduce the number of correlation we used steady-state genetic algorithm which is effective in optimization problem. We apply this method to distinguish specific pattern from similar coin patterns and estimate rotated angle between patterns. Our result leads us to the conclusion that proposed method performed faster than classical template matching

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.395-396
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• 2018

인터넷 쇼핑몰, 오프라인 매장에서 구입한 제품의 포토 리뷰를 블로그, 쇼핑몰에 올릴 때 얼굴 노출을 꺼려하여 직접 사진 처리 프로그램 등을 통해 얼굴을 가리거나 사진을 얼굴 부분까지 잘라 내는 등의 번거로운 작업을 거친 후 올리게 된다. 위와 같은 불편함을 해결하기 위해 쇼핑몰, 블로그 등 인터넷 매체를 통해 포토 리뷰를 작성 할 때 얼굴이 포함된 사진을 올리더라도 자동으로 얼굴 인식 후 의상에 어울리는 소품을 합성하여 구매자가 포토 리뷰를 올리기 편한 환경을 제공하고자 한다. 이를 위해 기본적인 얼굴 추적과 얼굴 특징 점을 기반으로 한 안경과 같은 소품 합성 등이 필요하다. 본 연구에서는 실시간으로 얼굴 및 특징점을 추출하고 이를 기반으로 얼굴에 소품을 합성하는 기본 기능을 구현하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.320-322
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• 2020

기계학습은 인공지능의 한 클래스로 최근 이미지 및 음성인식, 지능적 웹 검색, 자율 주행 자동차 등의 영역에서 성공적 발전을 바탕으로 우리의 일상에 폭넓게 이용되고 있다. 본 논문에서는 Keras 오픈소스 라이브러리를 이용해 딥러닝을 이용한 기계학습 기반의 동전 인식 소프트웨어를 구현하였고, 이를 이용해 동전 자동분류 스마트 저금통을 설계하였다. 동작 검증을 위하여 스마트 저금통의 모든 발생 이벤트는 Parse-server와 mongoDB를 이용하여 시각화 및 어플리케이션 및 웹사이트를 연결하였다.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.29-36
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• 2006

Tactile displays can provide useful information without disturbing others and are particularly useful for people with visual or auditory impairments. They can also complement other displays. In this paper, we present a new vibrotactile display device for wearable, mobile, and ubiquitous computing environments. The proposed vibrotactile device has a $5{\times}5$ array configuration for displaying complex information such as letters, numbers, and haptic patterns as well as simple directional ques and situation awareness alarms. Commercially available coin-type vibration motors are embedded vertically in flexible mounting pads in order to best localize vibrations on the skin. An embedded microprocessor controls the motors sequentially with an advanced tracing mode to increase recognition rate. User studies with the vibrotactile device on the top of the foot show 86.7% recognition rate for alphabet characters after some training. In addition, applying vibrotactile device to driving situation shows 83.9% recognition rate. We also propose some potentially useful application scenarios including Caller Identification for mobile phones and Navigation Aids for GPS systems while driving.