• Title/Summary/Keyword: pixel intensity series

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Exploiting Chaotic Feature Vector for Dynamic Textures Recognition

  • Wang, Yong;Hu, Shiqiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.11
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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.

Dye Leakage Measurement in Time Series Flucrescein Ocular Fundus Photographs (시계열 형광안저오진에서의 조경제 루출량 측정)

  • Kwon, Kap-Hyeon;Ha, Yeong-Ho;Kim, Soo-Joong
    • Journal of Biomedical Engineering Research
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    • v.12 no.4
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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.

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Similarity Measurement using Gabor Energy Feature and Mutual Information for Image Registration

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.27 no.6
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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.

Intensity Gradients-based Stereo Matching of Road Images (에지정보를 이용한 도로영상의 스테레오 정합)

  • 이기용;이준웅
    • Transactions of the Korean Society of Automotive Engineers
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    • v.11 no.1
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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.

Chaotic Features for Traffic Video Classification

  • Wang, Yong;Hu, Shiqiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.8
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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.

Radiographic analysis of the management of tooth extractions in head and neck-irradiated patients: a case series

  • Oliveira, Samanta V.;Vellei, Renata S.;Heguedusch, Daniele;Domaneschi, Carina;Costa, Claudio;Gallo, Camila de Barros
    • Imaging Science in Dentistry
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    • v.51 no.3
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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.

Chaotic Features for Dynamic Textures Recognition with Group Sparsity Representation

  • Luo, Xinbin;Fu, Shan;Wang, Yong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.11
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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.

The Study on Optimal Image Processing and Identifying Threshold Values for Enhancing the Accuracy of Damage Information from Natural Disasters (자연재해 피해정보 산출의 정확도 향상을 위한 최적 영상처리 및 임계치 결정에 관한 연구)

  • Seo, Jung-Taek;Kim, Kye-Hyun
    • Spatial Information Research
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    • v.19 no.5
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    • pp.1-11
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    • 2011
  • This study mainly focused on the method of accurately extracting damage information in the im agery change detection process using the constructed high resolution aerial im agery. Bongwha-gun in Gyungsangbuk-do which had been severely damaged from a localized torrential downpour at the end of July, 2008 was selected as study area. This study utilized aerial im agery having photographing scale of 30cm gray image of pre-disaster and 40cm color image of post-disaster. In order to correct errors from the differences of the image resolution of pre-/post-disaster and time series, the prelim inary phase of image processing techniques such as normalizing, contrast enhancement and equalizing were applied to reduce errors. The extent of the damage was calculated using one to one comparison of the intensity of each pixel of pre-/post-disaster im aged. In this step, threshold values which facilitate to extract the extent that damage investigator wants were applied by setting difference values of the intensity of pixel of pre-/post-disaster. The accuracy of optimal image processing and the result of threshold values were verified using the error matrix. The results of the study enabled the early exaction of the extents of the damages using the aerial imagery with identical characteristics. It was also possible to apply to various damage items for imagery change detection in case of utilizing multi-band im agery. Furthermore, more quantitative estimation of the dam ages would be possible with the use of numerous GIS layers such as land cover and cadastral maps.