摘要或動機

在我們週遭環境中常可見到許多種類的植物，然而可以叫出名字的卻少之又少，或許我們可以查閱植物百之類的書籍，但是這類書籍通常多不在手邊，就算有了植物百科，也不易翻到顯示該種植物的正確章節。假如我們可以將想要認識的植物葉片影像取得後，透過網路將該影像傳送至植物葉片資料庫查詢，經過電腦的自動分析辨識後，再將結果傳送回來，這樣不是比查閱植物百科方便多了嗎？本研究提出一種利用輸入葉片的影像來進行植物資料庫辨識查詢的方法，藉著兩階段處理的策略及最佳權重組合式的特徵值來調校系統，以達到較佳的整體辨識效能，從實驗測試的結果得知，我們的策略與方法確實有效，有82%的查詢葉片可以被精確的辨識出來，而每次查詢的平均反應時間只要17.22 秒。In our living environment, there are many kinds of plants, but we can only name a few. We may consult an encyclopedia about plants, we always can’t find any encyclopedia with us. Besides, even if we have one, it won’t be easy to find out the proper section or the exact page immediately. How should we solve this problem? One significant improvement can be expected if the plant recognition can be carried out by a computer. First, we take a picture of the unknown plant’s leaf. Then, we transmit this image into a leaf database to recognize. After the recognition we will get the answer easily. By using a computer-aided leaf recognition system, non-professionals can also identify many plant species. Isn’t it much more convenient than checking the encyclopedia? In this study, we present an efficient method for leaf database retrieval by inputting leaf images. We use a two-stage approach and combined features with optimized weight to adjust the system to get the best system performance. The result of the experiment shows that our approach is workable and efficient. 82% leaves of the query images can be recognized accurately. And in general, the average response time only takes 17.22 sec per query.