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dc.contributor.author張志豪en_US
dc.contributor.authorChih-Hao Changen_US
dc.contributor.author羅佩禎en_US
dc.contributor.authorPei-Chen Loen_US
dc.date.accessioned2014-12-12T02:24:14Z-
dc.date.available2014-12-12T02:24:14Z-
dc.date.issued1999en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#NT880591082en_US
dc.identifier.urihttp://hdl.handle.net/11536/66316-
dc.description.abstract摘 要: 本篇論文主要研究輪廓編碼方法(operational optimal Vertex-Based Shape Coding,VBSC)的編碼效能,並將它應用於影像邊界編碼與腦電波(EEG)資料壓縮上。對於輪廓型影像的處理上,我們首先使用邊界來表示它的輪廓,傳統的鏈碼(chain code)是一種簡單的邊界表示方法,但所得的壓縮比並不高。我們在論文中所介紹的方法(VBSC)其壓縮效能與實作參數有密切的關係。 文中我們首先研究影響壓縮效能和解碼後邊界品質的因素:「候選控制點集合寬度DM」與「可容許失真度Dmax」。除此之外,我們也會定義「影像輪廓複雜度」的量化指標,並討論在不同複雜度情況下,本方法所得到的壓縮效能。最後我們再將此方法應用在腦電波資料壓縮上。zh_TW
dc.description.abstractAbstract: This thesis aims to investigate the performance of an image coding method, operational optimal Vertex-Based Shape Coding (VBSC), applied to both the boundary coding and EEG (electroencephalograph) data compression. Boundary represen- tation is one of the tasks often required in the post-pro- cessing of a contour-type image. The conventional chain-code descriptor provides a simple way to represent a boundary, yet the compression ratio is low. Compression efficiency and per- formance of the VBSC introduced in this thesis highly depend on the implementation parameters. In this study, we first investigate the effect of two para- meters, the admissible control point width DM and the allowed distortion Dmax, on the compression efficacy and quality of the decoded boundary. In addition, a quantitative approach for mea-suring the complexity of a boundary is presented. Performance of the VBSC on several boundaries of different degrees of com- plexity is investigated. Finally, the method is applied to the EEG data compression. 第一章 簡介--------------------------------------1 1.1 背景---------------------------------------1 1.2 動機---------------------------------------1 1.3 章節的安排---------------------------------2 第二章 輪廓編碼的基本理論與方法------------------3 2.1 方法概觀-----------------------------------3 2.2 基本名詞定義-------------------------------4 2.2.1 候選控制點集合-------------------------4 2.2.2 編碼位元數-----------------------------7 2.2.3 失真度---------------------------------9 2.3 直接非環式座標最短路徑演算法-----------------10 第三章 輪廓編碼方法應用於輪廓型影像之探討--------15 3.1 鏈碼---------------------------------------15 3.2 影像輪廓複雜度-----------------------------18 3.3 誤差量測-----------------------------------22 3.4 結果與分析—輪廓型影像邊界之表示與編碼-----22 3.4.1 實驗參數(候選控制點集合寬度DM)---------22 3.4.2 實驗參數(可容許失真度Dmax)-------------26 3.5 不同複雜度之邊界的實驗結果-----------------30 第四章 輪廓編碼方法應用於腦電波訊號之探討--------36 4.1 腦電波訊號之介紹---------------------------36 4.2 誤差量測-----------------------------------37 4.3 結果與分析—腦電波訊號---------------------37 第五章 結論與未來展望----------------------------47 5.1 結論---------------------------------------47 5.2 未來展望-----------------------------------48 參考文獻 49en_US
dc.language.isozh_TWen_US
dc.subject輪廓zh_TW
dc.subject編碼zh_TW
dc.subject影像zh_TW
dc.subject腦電波zh_TW
dc.subjectImageen_US
dc.subjectCompressionen_US
dc.subjectVertex-Baseden_US
dc.subjectShape codingen_US
dc.subjectEEGen_US
dc.title輪廓編碼方法應用於影像與腦電波訊號壓縮zh_TW
dc.titleApplication of VBSC to Image and EEG signal Compressionen_US
dc.typeThesisen_US
dc.contributor.department電控工程研究所zh_TW
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