• 대한인간공학회지
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• 제19권1호
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• pp.91-100
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• 2000

In this paper the intent recognition system which recognizes the human's head movements as a simple non-verbal intent representation is presented. The system recognizes five basic intent representations. i.e., strong/weak affirmation. strong/weak negation, and ambiguity by image processing of nodding or shaking movements of head. The vision system for tracking the head movements is composed of CCD camera, image processing board and personal computer. The modified template matching method which replaces the reference image with the searched target image in the previous step is used for the robust tracking of the head movements. For the improvement of the processing speed, the searching is performed in the pyramid representation of the original image. By inspecting the variance of the head movement trajectories. we can recognizes the two basic intent representations - affirmation and negation. Also, by focusing the speed of the head movements, we can see the possibility which recognizes the strength of the intent representation.

• ETRI Journal
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• 제39권2호
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• pp.163-172
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• 2017

A high performance license plate recognition system (LPRS) is proposed in this work. The proposed LPRS is composed of the following three main stages: (i) plate region determination, (ii) character segmentation, and (iii) character recognition. During the plate region determination stage, the image is enhanced by image processing algorithms to increase system performance. The rectangular license plate region is obtained using edge-based image processing methods on the binarized image. With the help of skew correction, the plate region is prepared for the character segmentation stage. Characters are separated from each other using vertical projections on the plate region. Segmented characters are prepared for the character recognition stage by a thinning process. At the character recognition stage, a three-layer feedforward artificial neural network using a backpropagation learning algorithm is constructed and the characters are determined.

• 융합신호처리학회논문지
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• 제17권1호
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• pp.32-39
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• 2016

지능형 교통 시스템(Intelligent Transportation System, ITS)은 첨단기술을 사용하여 도로의 상황을 판단하고 적절한 처리를 수행하므로 이상적인 차량의 흐름을 유도하는 시스템이다. 교통상황에 대한 정보는 다양한 지점에서 측정되고 관리되어야 하므로 주로 컴퓨터를 이용한 영상이 사용된다. 컴퓨터를 이용한 영상처리는 실시간으로 다양한 교통 파라미터를 수집하기 용이한 방법이고, 기술들도 점점 발전하고 있다. 지능형 교통 시스템의 교통 파라미터 중 차량 검출은 기본적으로 매우 중요한 기술이다. 이를 위해 영상의 배경 차를 이용한 검출방법, 에지를 이용한 윤곽선 추출 방법 등의 기술들이 사용되고 있으나 검출률의 정확도에 문제점이 제기되고 있다. 본 논문에서는 레이블링에 의한 차량검출과 감지선을 이용한 영상처리 방법으로 차량을 검출하였다. 제안된 방법의 정확도를 확인하기 위해 국도와 고속도로 등 두 곳의 장소에서 20개의 수직, 수평 방향 영상을 수집하여 차량 계수를 측정하였다. 그 결과 수직 방향 92%, 수평 방향 91.3%의 검출률을 얻었다.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.53-64
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• 2023

Early detection of endometrial carcinoma in uterus is essential for effective treatment. Endometrial carcinoma is the worst kind of endometrium cancer among the others since it is considerably more likely to affect the additional parts of the body if not detected and treated early. Non-invasive medical computer vision, also known as medical image processing, is becoming increasingly essential in the clinical diagnosis of various diseases. Such techniques provide a tool for automatic image processing, allowing for an accurate and timely assessment of the lesion. One of the most difficult aspects of developing an effective automatic categorization system is the absence of huge datasets. Using image processing and deep learning, this article presented an artificial endometrium cancer diagnosis system. The processes in this study include gathering a dermoscopy images from the database, preprocessing, segmentation using hybrid Fuzzy C-Means (FCM) and optimizing the weights using the Whale Optimization Algorithm (WOA). The characteristics of the damaged endometrium cells are retrieved using the feature extraction approach after the Magnetic Resonance pictures have been segmented. The collected characteristics are classified using a deep learning-based methodology called Long Short-Term Memory (LSTM) and Bi-directional LSTM classifiers. After using the publicly accessible data set, suggested classifiers obtain an accuracy of 97% and segmentation accuracy of 93%.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.741-744
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• 1998

In the area of the multimedia computer, the demand for the image processing engineer is large. However, there are not many engineers capable of developing practical systems. To teach practical image processing techniques, we need an intergrated education systems which can efficiently present the image processing theory and, at the same time, provide interactive experiments for the theory presented. In this paper, we propose an integrated education systems for the image processing. It consists of the theory presentation systems and the experiment systems. The theory presentation systems uspports multimedia display functions and HTML. It is tightly integrated with the experiment systems which developed based on the integrated image processing algorithm development system called Hello-vision.

• 한국축산시설환경학회지
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• 제7권3호
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• pp.183-190
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• 2001

본 연구는 영상처리를 통한 보다 간편하고 정확한 젖소의 체중측정을 위해 수행되었다. 카메라와 개인용 컴퓨터를 이용하여 젖소의 영상을 받은 후 이의 화소 값들을 이용하였으며, 또한 여러 가지 방법으로 체중과의 관계를 회귀분석 방법을 하였다. 1. 본 실험의 결과 다중회귀식에 의한 계산체중, 화소표면적, 부피와 체증과의 상관계수는 각각 0.9424, 0.9439, 0.9651로 나타났으며, 젖소의 체중과 상관관계도가 높았다. 2. 실험에 이용된 젖소의 개체수를 50두이었지만, 각각 상태별 체형의 차이고 인하여 일관된 회귀식을 적용하기에는 정확도 문제에서 다소 문제가 있었다. 그래서 각 개체군으로 나누어서 연구할 필요가 있을 것으로 판단되었다. 3. 젖소의 체중 계측시간은 10초에 불과하지만 실험장치까지의 유도과정은 편균 한 마리에 10분 정도가 소요되었다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.465-468
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• 1997

A Study on Computer Assisted Diagnosis (CAD) system extract ing lung cancer part from Digital X-ray Computerized Tomography(CT) image is discussed in this paper. It is very crucial to segment the image of lung into the three organ area such as inside, outside and the hilum so that the variant image processing algorithm can be applied an each area respectively. In this paper, the efficient algorithm extracting lung cancer part is proposed with characterizing lung hilum part and its associated vessel patterns.

• 전기전자학회논문지
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• 제27권3호
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• pp.280-287
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• 2023

딥러닝의 발전은 컴퓨터 비전 문제를 해결할 수 있지만, 높은 정확도를 위해서는 대규모 데이터셋이 필요하다. 본 논문에서는 객체 바운딩 박스와 이미지 엣지 성분을 이용한 이미지 생성 기법을 제안한다. 객체 탐지를 통해 이미지 내의 객체 바운딩 박스를 추출하고 이미지 엣지 성분을 함께 이미지 생성모델의 입력값으로 사용하여 새로운 이미지 데이터를 생성한다. 실험 결과, 제안 기법으로 생성된 이미지는 이미지 품질 평가에서 소스 이미지와 유사한 품질을 보였고, 딥러닝 훈련과정에서도 좋은 성능을 보였다.

• 한국시뮬레이션학회논문지
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• 제9권3호
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• pp.53-64
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• 2000

With the recent outstanding advance in computer software and hardware, a number of researches to enhance the processing speed and the process accuracy has been undertaken in the field of container terminal industry,0 this paper, we propose a simulator for container image processing that can be used mainly for tile development of automatic container recognition system. The purpose of this study is to simulate many different algorithms and factors to extract information accurately on the captured container image.

• Genomics & Informatics
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• 제7권3호
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• pp.168-170
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• 2009

The explosion in biological data resulting from high-throughput experiments requires new software tools to manipulate and display pathways in a way that can integrate disparate sources of information. A visual Java-based CAD tool for drawing and annotating biological pathways with semiautomatic image-processing features is described in this paper. The result of the image-editing process is an XML file for the appropriate links. This tool integrates the pathway images and XML file sources. The system has facilities for linking graphical objects to external databases and is capable of reproducing existing visual representations of pathway maps.