• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권11호
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• pp.4137-4152
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• 2014

This paper investigates the description ability of chaotic feature vector to dynamic textures. First a chaotic feature and other features are calculated from each pixel intensity series. Then these features are combined to a chaotic feature vector. Therefore a video is modeled as a feature vector matrix. Next by the aid of bag of words framework, we explore the representation ability of the proposed chaotic feature vector. Finally we investigate recognition rate between different combinations of chaotic features. Experimental results show the merit of chaotic feature vector for pixel intensity series representation.

• 대한의용생체공학회:의공학회지
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• 제12권4호
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• pp.295-302
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• 1991

In this paper, the inter- and intra-frame distortions in the gray levels of a series of fluorescein ocular fundus photographs are corrected. For doing this, the background images are extracted from original images using the image blurring effect by decimation, and then shading corrected images are obtained by subtracting the background images from the original images pixel by pixel. In a series of fluorescein ocular fundus photographs, after the gray scale distoriton is corrected, the intensity volumes of dye leakage are measured and represented by a graph. These data may be useful for the prediction of prognosis and the therapeutic management.

• 대한원격탐사학회지
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• 제27권6호
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• pp.693-701
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• 2011

Image registration is an essential process to analyze the time series of satellite images for the purpose of image fusion and change detection. The Mutual Information (MI) is commonly used as similarity measure for image registration because of its robustness to noise. Due to the radiometric differences, it is not easy to apply MI to multi-temporal satellite images using directly the pixel intensity. Image features for MI are more abundantly obtained by employing a Gabor filter which varies adaptively with the filter characteristics such as filter size, frequency and orientation for each pixel. In this paper we employed Bidirectional Gabor Filter Energy (BGFE) defined by Gabor filter features and applied the BGFE to similarity measure calculation as an image feature for MI. The experiment results show that the proposed method is more robust than the conventional MI method combined with intensity or gradient magnitude.

• 한국자동차공학회논문집
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• 제11권1호
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• pp.201-210
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• 2003

In this paper, we propose a new binocular stereo correspondence method by maximizing a fitness formulated by integrating two constraints of edge similarity and disparity smoothness simultaneously. The proposed stereopsis focusing to measure distances to leading vehicles on roads uses intensity gradients as matching attribute. In contrast to the previous work of area-based stereo matching, in which matching unit is a pixel, the matching unit of the proposed method becomes an area itself which is obtained by selecting a series of pixels enclosed by two pixels on the left and right boundaries of an object. This approach allows us to cope with real-time processing and to avoid window size selection problems arising from conventional area-based stereo.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권8호
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• pp.2833-2850
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• 2014

This paper proposes a novel framework for traffic video classification based on chaotic features. First, each pixel intensity series in the video is modeled as a time series. Second, the chaos theory is employed to generate chaotic features. Each video is then represented by a feature vector matrix. Third, the mean shift clustering algorithm is used to cluster the feature vectors. Finally, the earth mover's distance (EMD) is employed to obtain a distance matrix by comparing the similarity based on the segmentation results. The distance matrix is transformed into a matching matrix, which is evaluated in the classification task. Experimental results show good traffic video classification performance, with robustness to environmental conditions, such as occlusions and variable lighting.

• Imaging Science in Dentistry
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• 제51권3호
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• pp.323-328
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• 2021

Tooth extraction after head and neck radiotherapy exposes patients to an increased risk for osteoradionecrosis of the jaw. This study reports the results of a radiographic analysis of bone neoformation after tooth extraction in a case series of patients who underwent radiation therapy. No patients developed osteoradionecrosis within a follow-up of 1 year. Complete mucosal repair was observed 30 days after surgery, while no sign of bone formation was observed 2 months after the dental extractions. Pixel intensity and fractal dimension image analyses only showed significant bone formation 12 months after the tooth extractions. These surgical procedures must follow a strict protocol that includes antibiotic prophylaxis and therapy and complete wound closure, since bone formation at the alveolar socket occurs at a slower pace in patients who have undergone head and neck radiotherapy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4556-4572
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• 2015

Dynamic texture (DT) recognition is a challenging problem in numerous applications. In this study, we propose a new algorithm for DT recognition based on group sparsity structure in conjunction with chaotic feature vector. Bag-of-words model is used to represent each video as a histogram of the chaotic feature vector, which is proposed to capture self-similarity property of the pixel intensity series. The recognition problem is then cast to a group sparsity model, which can be efficiently optimized through alternating direction method of multiplier algorithm. Experimental results show that the proposed method exhibited the best performance among several well-known DT modeling techniques.

• Spatial Information Research
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• 제19권5호
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• pp.1-11
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• 2011

본 연구에서는 기존에 구축된 고해상도 항공영상을 이용한 영상변화 탐지과정에서 보다 정확도 높은 풍수해 정보를 추출하는 방법에 대해 연구하였다. 연구 대상지역은 2008년 국지성 호우로 인해 큰 피해를 입은 경상북도 봉화군의 춘양면 일대를 선정하였다. 연구에서 활용된 항공영상은 해상도 30cm의 피해 전 흑백영상과 40cm의 피해 후 칼라 영상을 사용하였다. 영상분석에 있어 전처리 단계로서 피해 전 후 영상의 해상도 차이나 시계열적인 차이로 인한 오차 보정을 위하여 노멀라이징과 대비강조, 이퀄라이징의 기법을 적용하여 오차를 최소화하였다. 피해규모는 피해 전 후 영상을 구성하는 각 화소의 밝기 값을 1:1로 비교하는 방식으로 산정하였으며, 이 과정에서 피해 전 후 화소 밝기의 차이 값을 설정하여 조사자가 원하는 피해규모를 추출할 수 있도록 임계치를 설정하였다. 최적의 영상처리 및 임계치 선정의 결과는 오차매트릭스를 이용하여 확인하였다. 본 연구의 결과는 피해정보 추출 과정에서 동일한 제원을 갖는 항공영상을 이용하여 신속한 자연재해로 인한 피해규모의 산출이 가능하도록 하였다. 아울러 피해 전 후 다중밴드 영상을 추가로 확보하여 활용한다면 보다 다양한 피해항목에 대한 적용이 가능할 것으로 판단되었다. 나아가 토지피복분류도나 지적도 등 다양한 주제도를 영상변화 탐지에 활용한다면 정량적인 피해규모의 산출도 가능할 것으로 사료된다.