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    Please use this identifier to cite or link to this item: http://ccur.lib.ccu.edu.tw/handle/A095B0000Q/507


    Title: 以超像素為基礎之影像分割與區域合併;Superpixel-based Image Segmentation and Region Merging
    Authors: 王品文;WANG, PIN-WEN
    Contributors: 資訊管理系研究所
    Keywords: 影像分割;SLIC;超像素分割;HSV色彩特徵;image segmentation;SLIC;super pixel segmentation;HSV color feature
    Date: 2017
    Issue Date: 2019-07-17
    Publisher: 資訊管理系研究所
    Abstract: 在計算機視覺及影像處理的領域中,影像分割占了一個很重要的地位。影像?割技術雖持續?斷地被提出,然而,目前影像?割仍存有許多困難,而現今有些方法可以被應用於彩色影像之?割,大多的思維只將影像從一維空間擴充到三維色彩空間,並沒有討?色彩資?中所提供的其他相關訊息。因此,色彩空間對於影像分割也是一個很值得深入研究的主題之一。影像分割的目的,是希望能夠從影像中找出我們所感興趣的區域,或者是有意義的區域。超像素能夠取得像冗餘資訊,且降低後續處理任務複雜度,目前已受到了國內外研究者的日益關注。本研究提出一個分割方式,以SLIC超像素方法劃分影像為多個子區域,再依照本研究所提出之合併方法,結合紋理與 H、S、V、R、G和B色彩特徵進行特徵值相差最小的子區域合併,針對多物件、背景複雜與物件及背景差異性低等類型之彩色影像進行區域分割。根據實驗結果,本研究提出方式可成功分割複雜背景影像中之突出之物件。最後對本研究的方法與應用進行了結果討論和未來展望。
    In the field of computer vision and image processing, image segmentation occupies a very important position.Image segmentation technology is constantly being put forward, however, the current image cutting still has many difficulties, and now some methods can be applied to the color image segmentation, most of the thinking only the image from one-dimensional space expansion to three-dimensional color space, and did not discuss other relevant information provided in color data. Therefore, the color space for image segmentation is also a very worthy of one of the topics of in-depth study.The purpose of image segmentation is to be able to find areas of interest from the image, or a meaningful area. Superpixel can achieve redundant information, and reduce the complexity of follow-up processing tasks, has been the growing concern of researchers at home and abroad. This study presents a segmentation approach to the SLIC superpixel approach and the sub-regions with the smallest of the eigenvalues of the H, S, V, R, G and B color characteristics combined with the texture are combined with the sub-regions, and the background is complex and the background is complex. Object and background difference of low type of color image for regional segmentation. According to the experimental results, this study suggests that the way to successfully segment the complex objects in complex background images.Finally, the results of this study and application of the results of the discussion and future prospects.
    Appears in Collections:[資訊管理系研究所] 學位論文

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