• IEIE Transactions on Smart Processing and Computing
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• 제3권4호
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• pp.226-233
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• 2014

This paper presents an external light evasion method that rectifies the problem of misrecognition due to external lighting. The fundamental concept underlying the proposed method involves recognition of the differences between two images and elimination of the desynchronized external light by synchronizing the image sensor and inner light source of the optical touch screen. A range of artificial indoor light sources and natural sunlight are assessed. The proposed system synchronizes with a Vertical Synchronization (VSYNC) signal and the light source drive signal of the image sensor. Therefore, it can display synchronized light of the acquired image through the image sensor and remove external light that is not from the light source. A subtraction operation is used to find the differences and the absolute value of the result is utilized; hence, the order is irrelevant. The resulting image, which displays only a touched blob on the touchscreen, was created after image processing for coordination recognition and was then supplied to a coordination extraction algorithm.

• 음성과학
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• 제12권1호
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• pp.135-142
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• 2005

An important aspect of video indexing is the ability to segment video into meaningful segments, i.e., content-based video segmentation. Since the audio signal in the sound track is synchronized with image sequences in the video program, a speech signal in the sound track can be used to segment video into meaningful segments. In this paper, we propose a new approach to content-based video segmentation. This approach uses closed caption to construct a recognition network for speech recognition. Accurate time information for video segmentation is then obtained from the speech recognition process. For the video segmentation experiment for TV news programs, we made 56 video summaries successfully from 57 TV news stories. It demonstrates that the proposed scheme is very promising for content-based video segmentation.

• 융합신호처리학회논문지
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• 제11권3호
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• pp.221-225
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• 2010

This paper presents the preliminary study of an interactive rehabilitation support system for both dementia patients and their caregivers, the goal of which is to improve the quality of life(QOL) of the patients suffering from dementia through virtual interaction. To achieve the virtual interaction, three kinds of recognition modules for speech, facial image and pen-mouse gesture are studied. The results of both practical tests and questionnaire surveys show that the proposed system had to be further improved, especially in both speech recognition and user interface for real-world applications. The surveys also revealed that the pen-mouse gesture recognition, as one of possible interactive aids, show us a probability to support weakness of speech recognition.

• 한국재난정보학회 논문집
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• 제12권1호
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• pp.47-53
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• 2016

본 연구에서 개발 하고자 하는 기술은 3차원 영상인식을 위한 다중 영상매핑 시스템에 관한 연구 로 기존 통합 관제 시스템에 적용하거나 실시간 영상 관제 시스템 구축의 중심기술이 되고자 하는 것을 목적으로 한다. 따라서, 본 연구에서 계획한 다중 영상 매핑 시스템이 개발된다면, CCTV카메라기술과 네트워크 기술만으로도 즉, 다수의 연계된 시스템을 구축하지 않아도 보안담당자가 실제 순찰하면서 관제하는 서비스를 제공할 것이며, 필요하다면 타 시스템과 연계하여 순찰자의 의도를 반영할 수 있는 시스템으로 발전시킬 것이다. 또한, 이러한 시스템이 개발된다면 보안담당자의 재난 및 안전위협을 초래하는 상황에서 벗어날 수 있는 동시에 비교적 소규모의 경제력을 가진 사용자에게도 서비스를 제공할 수 있을 것으로 기대된다.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.48-54
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• 2023

Nowadays, a blind man finds it very difficult to cross the roads. They should be very vigilant with every step they take. To resolve this problem, Convolutional Neural Networks(CNN) is a best method to analyse the data and automate the model without intervention of human being. In this work, a traffic signal recognition system is designed using CNN for the visually impaired. To provide a safe walking environment, a voice message is given according to light state and timer state at that instance. The developed model consists of two phases, in the first phase the CNN model is trained to classify different images captured from traffic signals. Common Objects in Context (COCO) labelled dataset is used, which includes images of different classes like traffic lights, bicycles, cars etc. The traffic light object will be detected using this labelled dataset with help of object detection model. The CNN model detects the color of the traffic light and timer displayed on the traffic image. In the second phase, from the detected color of the light and timer value a text message is generated and sent to the text-to-speech conversion model to make voice guidance for the blind person. The developed traffic light recognition model recognizes traffic light color and countdown timer displayed on the signal for safe signal crossing. The countdown timer displayed on the signal was not considered in existing models which is very useful. The proposed model has given accurate results in different scenarios when compared to other models.

• 한국정보통신학회논문지
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• 제18권1호
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• pp.155-161
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• 2014

본 연구는 사용자의 감성을 효율적으로 유도하는 실시간 감성 이미지 콘텐츠 플레이어를 제안한다. 감성 이미지 콘텐츠 플레이어는 실시간으로 이미지 콘텐츠의 명도, 채도에 변화를 줌으로써 사용자의 감성에 따라 효율적으로 감성 유도가 가능하도록 설계하였다. 감성인식 부분은 자율신경계 기반의 맥파, 피부온도, 피부저항의 생체신호를 활용하였다. 사용된 감성 콘텐츠 이미지는 국제적 정서체계(IAPS)에서 분류된 9가지 감성영역의 이미지를 적용하였다. 실험결과로 감성 이미지 콘텐츠 플레이어를 통해 이미지의 감성 상태에 맞는 사용자의 감성이 10% 더 정확하게 유도되었다. 감성 콘텐츠 플레이어는 실시간으로 감성 반영을 통해 사용자와 콘텐츠간의 감성적 교감을 증대시킬 것으로 기대된다.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
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• pp.11-14
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• 2007

인간과 컴퓨터간의 상호교류 하는데 있어서 감정 인식은 필수라 하겠다. 그래서 본 논문에서는 음성 신호 및 얼굴 영상을 BL(Bayesian Learning)과 PCA(Principal Component Analysis)에 적용하여 5가지 감정 (Normal, Happy, Sad, Anger, Surprise) 으로 패턴 분류하였다. 그리고 각각 신호의 단점을 보완하고 인식률을 높이기 위해 결정 융합 방법과 특징 융합 방법을 이용하여 감정융합을 실행하였다. 결정 융합 방법은 각각 인식 시스템을 통해 얻어진 인식 결과 값을 퍼지 소속 함수에 적용하여 감정 융합하였으며, 특정 융합 방법은 SFS(Sequential Forward Selection)특정 선택 방법을 통해 우수한 특정들을 선택한 후 MLP(Multi Layer Perceptron) 기반 신경망(Neural Networks)에 적용하여 감정 융합을 실행하였다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.585-590
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• 2000

Recently, It is gradually raised necessity that thickness of thin film is measured accuracy and managed in industrial circles and medical world. Ultrasonic Signal processing method is likely to become a very powerful method for NDE method of detection of microdefects and thickness measurement of thin film below the limit of Ultrasonic distance resolution in the opaque materials, provides useful information that cannot be obtained by a conventional measuring system. In the present research, considering a thin film below the limit of ultrasonic distance resolution sandwiched between three substances as acoustical analysis model, demonstrated the usefulness of ultrasonic Signal processing technique using information of ultrasonic frequency for NDE of measurements of thin film thickness, sound velocity, and step height, regardless of interference phenomenon. Numeral information was deduced and quantified effective information from the image. Also, pattern recognition of a defected input image was performed by neural network algorithm. Input pattern of various numeral was composed combinationally, and then, it was studied by neural network. Furthermore, possibility of pattern recognition was confirmed on artifical defected input data formed by simulation. Finally, application on unknown input pattern was also examined.

• 융합신호처리학회논문지
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• 제3권2호
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• pp.15-22
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• 2002

본 논문에서는 보안시스템에 적용할 수 있는 얼굴인식 알고리즘을 제안하였다 얼굴인식을 위해 기존에는 얼굴특징의 거리와 각도를 이용한데 반해, 제안한 방법에서는 명암영상을 직접적인 입력으로 사용하고, 기준영상과 입력영상의 두 염색체를 비교하여 적응도가 가장 좋은 개체를 선택하는 유전자 알고리즘을 사용하였고, 모의실험을 통해 성능을 검증하였다.

• 한국안전학회지
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• 제23권6호
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• pp.164-170
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• 2008

This research was verified detection way of intercept vehicles and performance evaluation after system installation using image detector as detection way of ground installation. By image recognition algorithm was on the trace of moving orbit of violation vehicles for detection way of intercept vehicles. When moving orbit is located special site, utilized geometric image calibration and DC-notch filter. These are cognitive system of license plate by making signal. Then, Bright Evidence Detection and Dark Evidence Detection were applied to after mixing. It is applied to way of Backward tracking for detection way of intercept vehicles. After the field evaluation of developed system, it should be analyzed the more high than recognition rate of minimum standards 80%. It should rise in the estimation of the site applicability is highly from now.