運用以內容為基礎之影像擷取於藥物辨識之研究
中文摘要
近年來知識水準的提升以及發生的一些重大藥物疏失事件，民眾對於 藥物資訊與藥物安全的需求與日劇增。可是要上網查詢這些藥物資訊，往往還是只能藉由輸入文字的方式去查詢。基於資訊科技的進步與 文字查詢的不便等各種因素，本論文運用以內容為基礎的影像擷取方 法，建置一個藥物實體影像辨識系統，提供醫療人員或民眾運用數位 相機等方式取得數位影像後，經由自動化的方式擷取藥物影像的內容 特徵進行分析，然後回饋使用者相關的藥物資訊。簡化了藥物辨識系 統的操作程序，增加民眾對藥物辨識系統的使用意願及方便性。
本論文探討影響藥物影像辨識的重要因素，並以 GIFT 程式為範本針 對藥物的顏色、紋理、旋轉、遠近等因素進行驗證並提出本論文的作 法與改進方式，在超過七百張藥物影像的測試下，最後成功建立了一 套藥物實體影像辨識系統，其平均檢索成功率（Ｓ）可達 80.11 ％，膠囊可達 94.92 ％。期望在未來可供藥物影像辨識研究上的參考並能 有助於藥物辨識系統新介面的研發，擺脫傳統文字查詢的不便。
Applying Content Based Image Retrieval to Drug Identification Research
英文摘要
In recent years, with the improvement of knowledge level and some serious medication errors happened, people require drug information and safety increasingly. Mostly, we can only searc h drug information by typing some key words from Internet. Based on the advancement of inf ormation technology and inconvenience of key word search, this thesis applied content-based i mage retrieval to build a Real Drug Image Identification System (RDIIS). This system allows health care personnel and the public upload digital images. After catching automatically the co ntent of drug images, system will feed back users with relevant drug information. It simplifies the operation of drug identification system and increases the desire and convenience for the pu blic to use it.
This thesis discussed many important factors which may influence drug image identification.
We used GIFT as a model and tested many factors including color, texture, rotation and distan ce then proposed solution for improvements. In this study, we tested more than seven hundred s drug images and successfully build a RDIIS whose average of search success ratio ( Ｓ ) is a ble to get up to 80.11 ％ and capsule ratio is reached 94.92 ％ . We expect that this thesis can be a reference for other drug image identification research and help the development of new us er interface in order to get rid of the inconvenience of the traditional key word searching.
