教師資料查詢 | 類別: 研究報告 | 教師: 周建興 Chien-hsing Chou (瀏覽個人網頁)

標題:應用模糊群聚演算法與群聚驗證之消失點偵測研究
學年101
學期1
出版(發表)日期2012/08/01
作品名稱應用模糊群聚演算法與群聚驗證之消失點偵測研究
作品名稱(其他語言)Vanishing-Point Detection Based on Fuzzy Clustering Algorithm and New Clustering Validity Measure
著者周建興
單位淡江大學電機工程學系
描述計畫編號NSC101-2221-E032-055 ;
研究期間201208~201307 ;
研究經費483,000
委託單位行政院國家科學委員會
摘要3D 立體影像在未來的科技生活中,扮演越來越重要的角色,有關3D 影像的開發以 及應用,是目前相當受到重視的研究方向。此計畫主要探討的研究主題,是使用深度 估測法將單張2D 影像轉換成3D 影像。深度估測法最重要的目標,就是從一張影像中 估測出場景的深度圖;然後使用原始影像與深度圖產生出左眼與右眼的影像。在整個 流程中有兩個最重要的步驟,一個是將前景物體切割出來,另一個是指派適當的深度 值給所有的物體。但是,要在所有類型的影像中,成功地切割出前景物體,或是估計 出影像的深度圖,都可說是十分困難的任務。 在此計畫中,我們首先結合模糊群聚演算法,提出一個影像前處理方法。所提出 的前處理方法可以在影像中擷取出較關鍵的邊界資訊,以偵測出消失線與消失點的位 置。此外,在這計畫中,我們也預計提出一個全新的群聚驗證演算法,這個群聚驗證 演算法將評估群聚的面積是否相近,以估測出合適的群聚數目。依據估測到的群聚數 目,搭配所提出的前處理方法,我們能更準確地定位出消失點與消失線的位置,還能 進一步提供影像中前景與背景的資訊,有助於建立正確的深度圖。;Three-dimensional images will play an increasingly important role in the future of science and technology. The development and application of 3D images, therefore, is currently a major focus of research. This project focuses on converting a single 2D image into a 3D image using the depth-estimation method. The objective of a depth-estimation method is estimating the depth map of a scene from an image; the left-eye and right-eye images can then be produced using the original image and depth map. Two critical steps are included in this process. One segments the foreground objects and background; the other assigns appropriate depth value to all objects. However, it is difficult to design a method to segment foreground objects and generate depth maps for all types of images. In combination with the fuzzy clustering algorithm, this project proposes an image-preprocessing method. Critical edge information can thus be extracted from an image to locate vanishing lines and the vanishing point. To estimate an appropriate initial cluster number, this project also proposes a new clustering validity measure to assess the similarity of cluster areas. By applying the estimated cluster number and the proposed processing method, we can not only accurately discover the location of the vanishing point and vanishing lines, but also further provide useful information for image segmentation.
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