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研究生:魏甫錦
研究生(外文):Fu-Jin Wei
論文名稱:種子影像資料庫之建構與系統分析
論文名稱(外文):Construction and System Analysis of the Seed Image Database
指導教授:胡凱康王裕文王裕文引用關係
指導教授(外文):Kae-Kang HwuYue-Wen Wang
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:農藝學研究所
學門:農業科學學門
學類:一般農業學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:中文
中文關鍵詞:種子影像資料庫建構系統分析
外文關鍵詞:seedimagedatabaseconstructionsystem analysisDELTAQTVR3D
相關次數:
  • 被引用被引用:3
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  • 下載下載:35
  • 收藏至我的研究室書目清單書目收藏:3
種子辨識的技術,在不同領域的各個應用層次上,如:分類學家、生態學家及種子檢查人員等,扮演著核心技術的角色。但在實際操作上常會遇到下列問題,如:辨識人才訓練不易、常見作物和雜草種子的圖鑑及文獻散列、種子辨識之專業書籍少有、一般分類檢索方式易生困擾或術語解釋不同等問題。
基於資訊科技對於處理重複性及需要大量的記憶工作,具有優越的長處,而資訊系統在分類學上的應用,已有近40年的歷史 (Pankhurst, 1970),並且已有類似的成功實例可供參考 (Chang, et al., 2000)。故本研究的目標為整理收集相關的種子分類特徵,配合現代資訊科技的發展,結合電腦影像技術,建立種子鑑識影像資料庫系統,以協助種子的鑑識。
經過商用資料庫系統比較系統效益與資料庫擴充,目前已被Taxonomy Database Working Group (TDWG)承認的標準分類資料交換格式DEscription Language TAxonomy (DELTA),有相對性較佳的優點,據此選為本研究資料庫系統開發的平台。參考已發表的分類資料庫實例 (Dallwitz, 2001),採用其編輯及管理系統DELTA System (Dallwitz, et al., 2000)並加入中文說明,建立「種子影像資料庫」。本資料庫目前已收錄材料為來自International Seed Testing Association (ISTA)的68個物種,其物種涵蓋的科屬廣泛,以禾本科最多,有25個物種。
種子影像取得方面,每個物種種子並拍攝至少3張以上不等的照片,並按照文獻所記載特徵部位取得特寫。另外,分類每一個特徵選項並配有相關的圖片說明。
資料庫建立後,選用特徵按類別,經過INTKEY (DELTA 系統中的檢索程式)的分群演算,分離效果 (Separating power)最佳者依序為長寬、形狀及表面特徵,種皮衍生物 (毛、芒或翅)則與表面特徵不相上下。
資料庫及檢索系統經過53位使用者試用結果,平均每次輸入約3個條件就會得到答案。而由選用特徵及其順序數據得知:1. 不論正確與否,各特徵被使用的次數無顯著差異; 2. 較明顯的特徵,被選用次數較高。顯示本系統仍有部分檢索特徵說明需要改進。
檢索結果影像比對確認部分,目前已建立一部份種子3D虛擬實境 (Virtual Reality)影像,未來配合3D種子影像的取得,有助於操作者比對樣本,可使本系統檢索結果之正確性更為提高。

The identification of seed is among the main tasks of taxonomy study, ecological research as well as seed testing. The common problems encountered in the identification of seed were the training of the personnel, the shortage of reference and atlas of the seeds, and the lack of consistency of the terminology for describing the characteristics of the seed.
The information technology has been proved to be an excellent tool for handling repetitive tasks and processing huge information. The application of information technology in the taxonomy can be traced back forty years ago. Several real world applications have been published and put into work. The primary objective of this research is to incorporate the latest development of the information technology including computer image, database system and front-end user interface into a integrated seed image database system to assist the identification of the seed.
The file format developed by DELTA (DEscription Language TAxonomy) recognized by the Taxonomy Database Working Group (TDWG) as one of the standard taxonomic data exchange format was chosen as the file format in this research. The full package DELTA system developed by Dallwitz (2000) was selected as the primary editing and database management tool for the construction of the seed image database system. Seed samples of sixty-eight species received from the International Seed Testing Association (ISTA) were used to construct the database. The seed samples provide an ample coverage of the plant kingdom with emphasis on the grasses, 25 species from poaceae were included in the sample.
The seed images were taken at least from three different angles of view for each species in the sample for the construction of the image database. The image of the specific morphological characteristics in related reference was taken accordingly. To better assist user in using the system, a diagram of each characteristic was created and shown during the operation of the program in the appropriate time.
After the database been constructed, the best separating power of the keys calculated with the INTKEY (the indexing and querying program of the DLETA system) was found to be in the order of length/width, shape and surface characters. The seed coat epidermal derivatives (hair, awn or wing) exhibit similar power as the surface characters.
Fifty-three users, who do not have any experience in the identification of seed, evaluated the constructed database along with the query system. The result found on average after three queries, an answer will be reached. The selected key and their order been selected indicated: 1. There was no difference in the number of the each key been queried. 2. the more common characters were more likely to be queried. The result suggested the description of each key needed to be revised to give user better direction.
In the assistance of the visual confirmation of the queried results, three dimension images with virtual reality display were built for part of the sample, it appeared to be a good mean in assisting the user making final decision. It should be included in the system.

一、 前言......................................1
二、 前人研究..................................4
(一) 描述用語................................4
(二) 檢索系統................................7
1. 推論機制....................................8
2. 資料結構...................................10
三、 材料與方法...............................13
(一) 材料...................................13
1. 種子標本...................................13
2. 影像拍攝...................................14
3. 資料庫及檢索系統...........................14
(二) 方法...................................15
1. 特徵值測量、觀察與紀錄.....................17
2. 影像擷取格式及處理.........................19
3. 資料建檔...................................20
4. 效能測試...................................23
四、 結果.....................................24
(一) 影像拍攝...............................24
(二) 檢索系統INTKEY.........................26
(三) 效能測試...............................29
五、 討論.....................................31
(一) 現有系統分析...........................31
1. 特徵值選用與輸入...........................31
2. 影像取得...................................32
3. 中文字碼的問題.............................33
4. 試用結果討論...............................34
(二) 目前DELTA相關研究......................35
1. 與DELTA相似之分類資料庫格式NEXUS及LUCID....37
(三) 3D種子影像取得.........................37
1. 拍攝.......................................38
2. 製成虛擬真實動畫檔.........................39
(四) 系統相關的現況及未來...................40
1. 資料交換...................................40
2. 自動辨識...................................41
中文摘要......................................43
Summary.......................................44
參考文獻......................................46
附錄..........................................50
附錄1. 特徵列表 Character List................50
附錄3. MS Access分類資料庫(.mdb)欄位列表......51
附錄2. VBA巨集程式............................51

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