積分圖形之自適性閥值方法應用於三維距離資料壓縮 = Compressio...
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  • 積分圖形之自適性閥值方法應用於三維距離資料壓縮 = Compression of 3D range data with adaptive thresholding using the Integral Image
  • 紀錄類型: 書目-語言資料,印刷品 : 單行本
    並列題名: Compression of 3D range data with adaptive thresholding using the Integral Image
    作者: 吳斌,
    其他團體作者: 國立高雄大學
    出版地: [高雄市]
    出版者: 撰者;
    出版年: 民100[2011]
    面頁冊數: 35葉圖,表格 : 30公分;
    標題: 有損資料壓縮
    標題: Lossy compression
    電子資源: http://handle.ncl.edu.tw/11296/ndltd/72588365981423135390
    附註: 參考書目:葉34-35
    附註: 內容為英文
    摘要註: 電腦視覺是一門仍有廣大進步空間的領域,因為其應用本身,必需要收集大量的環境資料,來提供足夠的資訊量,才能進行視覺相關應用的計算,也因其需要大量的資料,視覺相關應用需要花費較長的計算時間。隨著資訊設備在同價格上能提供更多計算量,並且體積越來越小的局面下,電腦視覺所能進行的應用也越來越廣泛。3D場景的視覺重建,需要3D距離資料,其資料量十分龐大,無論是要進行保存、計算或是傳送,均面臨各種效能問題,因此需要一種破壞性資料壓縮,於儀器收集進來龐大的原始資料盡可能萃取出必要的以及丟棄不必要的資訊。在本文中提出了一種稱之為Compression of 3D range data of adaptive thresholding using the Integral Image的破壞性資料壓縮方法。此方法具有創意性並且可以將舊有的二維方法延伸至三維,可以在破壞性資料壓縮的同時,保持大量三維物件邊緣資訊,減少關鍵視覺資訊上的失真。 Computer vision still has many research areas for improvement. A lot of its applications require collection of environmental information. A huge amount of information may be used for applications related to visual computing. Due to the huge amount of data, performance of vision related applications may often require a lot of time. Nevertheless, with the advancement in hardware, processing powers have increased and the applications of computer vision can become increasingly popular.3D distance information is needed to reconstruct a 3D scene. The amount of data for the 3D coordinates of a scene may be very large. So, it is difficult to save or transmit the data. Computers face performance issues during the processing of large amount of data. Therefore, a destructive data compression method may be required to reduce the amount of data. Based on the raw data imported from instruments, we want to extract the necessary information and discard the rest. In this paper, the compression of 3D range data with adaptive thresholding using the integral image data compression method for destructive data compression is proposed. This is a creative way and extends old method for 2D image to 3D that can maintain a large number of three-dimensional edge information of object while processing destructive data compression. It can reduce the reservation on the critical information for human’s eye.
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310002131343 博碩士論文區(二樓) 不外借資料 學位論文 TH 008M/0019 464103 2603 2011 一般使用(Normal) 在架 0
310002131350 博碩士論文區(二樓) 不外借資料 學位論文 TH 008M/0019 464103 2603 2011 c.2 一般使用(Normal) 在架 0
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