• Journal of the Institute of Convergence Signal Processing
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• v.9 no.3
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• pp.188-194
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• 2008

We propose the new method for the traffic signs recognition that is one of the DAS(Driving assistance system) in the intelligent vehicle. Our approach estimates a varied degree by using a geometric method from the varied traffic signs in noise, rotation and size, and extracts the recognition symbol from the compensated traffic sign for a recognition by using the sequential color-based clustering. This proposed clustering method classify the traffic sign into the attention, regulation, indication, and auxiliary class. Also, The circular tracing method is used for the final traffic sign recognition. To evaluate the effectiveness of the proposed method, varied traffic signs were built. As a result, The proposed method show that the 95 % recognition rate for a single variation, and 93 % recognition rate for a mixed variation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.10a
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• pp.168-168
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• 2003

• Journal of the Korean Society of Radiology
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• v.7 no.1
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• pp.9-15
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• 2013

In this study, texture feature analysis (TFA) algorithm to automatic recognition of liver disease suggests by utilizing computed tomography (CT), by applying the algorithm computer-aided diagnosis (CAD) of hepatocellular carcinoma (HCC) design. Proposed the performance of each algorithm was to comparison and evaluation. In the HCC image, set up region of analysis (ROA, window size was $40{\times}40$ pixels) and by calculating the figures for TFA algorithm of the six parameters (average gray level, average contrast, measure of smoothness, skewness, measure of uniformity, entropy) HCC recognition rate were calculated. As a result, TFA was found to be significant as a measure of HCC recognition rate. Measure of uniformity was the most recognition. Average contrast, measure of smoothness, and skewness were relatively high, and average gray level, entropy showed a relatively low recognition rate of the parameters. In this regard, showed high recognition algorithms (a maximum of 97.14%, a minimum of 82.86%) use the determining HCC imaging lesions and assist early diagnosis of clinic. If this use to therapy, the diagnostic efficiency of clinical early diagnosis better than before. Later, after add the effective and quantitative analysis, criteria research for generalized of disease recognition is needed to be considered.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1241-1248
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• 2019

In this paper, an auxiliary device was implemented to help blind people more safely from obstacles or risk factors while walking. The ultrasonic sensors detect obstacles in the front, so that the noise gap and the vibration intensity of the buzzer can be heard differently by distance and angle, and so the situation can be perceived by pedestrians. When the ambient light becomes darker than the light intensity set using the CdS resistance value of the light sensor, the LED automatically turns on, makes it easier for pedestrians to recognize the position of the auxiliary device through buzzer if the pedestrian misses the aid using the gyro sensor's slope. Moreover, the location and situation of the blind were transmitted to the caregiver to check safety and behavior using GPS and Bluetooth.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.1001-1010
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• 2021

Normal people are not deeply aware of their dependence on sight when eating. However, since the visually impaired do not know what kind of food is on the table, the assistant next to them holds the blind spoon and explains the position of the food in a clockwise direction, front and rear, left and right, etc. In this paper, we describe the development of a meal assistance system that recognizes each food image and announces the name of the food by voice when a visually impaired person looks at their table using a smartphone camera. This system extracts the food on which the spoon is placed through the YOLO model that has learned the image of food and tableware (spoon), recognizes what the food is, and notifies it by voice. Through this system, it is expected that the visually impaired will be able to eat without the help of a meal assistant, thereby increasing their self-reliance and satisfaction.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.392-395
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• 2020

최근 미디어 기술의 발달에 따라 문서 형태로 제공되던 기존의 서비스가 다양한 형태로 제공되고 있다. 그 중 요리의 경우, 사용자의 노하우가 부족하면 간접적인 도움으로는 한계가 있기 때문에 주방보조시스템을 구성하여 사용자에게 직접적인 도움을 제공하고자 하며 재료를 손질하거나 불을 사용할 때 시스템의 도움을 받을 수 있도록 했다. 우선 재료를 손질하는 경우 웹캠이나 핸드폰을 이용하여 요리 재료를 인식하고 사용자가 잘라야 할 요리 재료에 절취선을 제공하여 특별한 도구 없이도 시각적인 도움을 받을 수 있도록 구현했으며 요리 재료를 인식하고 절취선을 제공하기 위해 물체 인식, Object Segmentation 알고리즘을 사용하여 재료의 영역을 파악한 뒤 OpenCV 라이브러리를 통해 실시간으로 절취선을 생성한다. 불을 사용하는 경우 적외선 온도 센서가 지속적으로 요리의 온도를 측정하여 UI에 표시한다. 이러한 서비스를 요리의 진행상태와 연동하여 제공함으로써 요리에 필요한 정보를 한눈에 확인할 수 있고 차후 가전제품과 연동되면 다양한 레시피를 누구나 편리하게 사용할 수 있을 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.429-431
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• 2022

하지 웨어러블 로봇의 근력 보조 성능을 극대화하기 위해서는 착용자의 보행 상태를 인식하는 보행 위상 추정 기술이 필수적으로 요구된다. 본 논문에서는 착용자의 보행 속도 변화 및 착용자 간 보행 특성 차이에도 강인하게 보행 위상을 추정할 수 있는 LSTM 기반 보행 위상 강건 인식 기술을 개발하였다. 웨어러블 고관절 보조 로봇을 착용한 총 5명의 트레드밀 및 실외 overground의 보행 센서 정보를 바탕으로 학습을 수행하였다. 저속 및 고속 보행을 포함한 다양한 보행 속도에서 정밀한 보행 위상 추정이 가능한 웨어러블 센서 조합을 도출하였고, 보행 위상 인식 정밀성은 5-Fold Cross Validation 기준 RMSE 약 1.68% 수준의 결과를 얻을 수 있었다.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.585-588
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• 1998

현재의 언어자동인식은 목소리의 음성 정보와 얼굴영상의 화상정보를 병행처리하여 초기의 음성 정보만을 처리한 경우보다 높은 인식률을 가져왔다. 이러한 연구는 언어의 인식에서 뿐만 아니라, 신체가 부자연스러운 장애니에게는 간단한 의미 전달의 수단이나 각종 재활보조기기의 제어 등에도 매우 유용하게 활용될 수 있다. 음성정보처리를 배제한 영상정보처리 면에서, 본 논문의 대상이 되는 장애인은 신체의 부자연스러움으로 인해 처리되는 얼굴의 영상이 정상인과 같은 바른 자세가 되지 못하고, 기울어진다든지 틀어져서 기존의 방법들로는 정상인보다 현저히 낮은 입모양의 인식률을 보인다. 본 논문에서는 기존의 방법들과는 달리 청색 표식을 이용한 색상불할법과 라벨링을 통해 입 모양을 인식하는 방법을 제안하였으며, 이는 장애인과 같은 기울어진 얼굴영상에 대해서도 정상인과 같은 입 모양 인식률을 나타내었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.231-234
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• 2002

This paper considers a system related to biometrics which can control entrance and exit based on pattern and feature of a tooth. It is aimed at research and development of a controling entrance and exit system connected advanced image understanding technique using a tooth recognition that treats a tooth of simple and fixed structure. We think that the system is applied(or utilized) as pre-step or assistance means of face recognition and expect that the system achieves greatly effective results.

• Journal of the Korean Society of Radiology
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• v.10 no.2
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• pp.81-87
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• 2016

In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some fatty liver patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of fatty liver. As the results of examining over 30 example CT images of fatty liver, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including Average Gray Level, Entropy 96.67%, Skewness 93.33%, and Smoothness while others showed a little low disease recognition rate: 83.33% for Uniformity 86.67% and for Average Contrast 80%. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of fatty liver and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading.