基於影像分析之水稻飛蝨偵測

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姓名

李庭瑜(Ting-Yu Lee) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

基於影像分析之水稻飛蝨偵測
(Detection of Rice Planthopper by Image Processing in Rice Field)

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摘要(中)

在亞洲，每一年飛蝨(Rice Planthopper, RPH)對稻田都有著相當嚴重的侵害，尤其是在東南亞地區，台灣的稻田也是幾乎每年都遭受飛蝨的侵害所苦。飛蝨極小且易散播，所以能有效掌握飛蝨的出沒，才能最快的預防飛蝨的擴大，輔助農民觀測飛蝨的出沒情況，在對的時機點噴灑農藥才是最有幫助的方式。在複雜的稻田影像中，影像處理能夠有效的幫助發現飛蝨，首先在高畫素的影像中進行裁切，我們只關注位在中央感興趣的稻株，切割掉左右兩邊的影像，其次在中央感興趣的植株上尋找飛蝨，在此對影像中的物件做色彩的分析，將色彩資訊的相對關係作為分類依據，排除非飛蝨的pixel，最後得到含有飛蝨及其疑似物的二值化影像，並對二值化影像進行標記，標記出飛蝨便於觀測。這是一套能快速取得感興趣區域的方法，留下完整的飛蝨影像，並且能夠降低後續欲對飛蝨進行應用處理的負擔，減少處理的時間。

摘要(英)

Rice Planthopper (RPH) infestation in paddy field is a serious disaster in Asia almost every year, particularly Southeast Asia. It is still suffered RPHs in Taiwan. RPHs are very small and spread easily. Since control RPHs growth is effective to prevent RPH infestation, it is important for farmer to sprinkle pesticides at right time before RPH growth. Preprocess image that complex field scene is helpful to find RPH. First, get rectangle region of interest (ROI) in HD image. We focus on the rice stem in the middle of image and remove the both side in the image. Then, get RPHs in the ROI. Get color information on objects in the ROI and do color analysis. Finally, use decision tree algorithm by relative of color information to get binary image that contain RPHs and something like that and remove pixels without RPHs and label RPHs to observe easily in the binary. This paper propose a method that get ROI quickly. It is useful to reduce executing time and loading for follow-up action and obtain clearly RPH ROI image.

關鍵字(中)

★ 影像處理
★ 感興趣區域
★ 水稻飛蝨

關鍵字(英)

★ Image Processing
★ ROI
★ Rice Planthopper (RPH)

論文目次

摘要 I
ABSTRACT II
TABLE OF CONTENTS III
LIST OF FIGURES IV
LIST OF TABLES V
CHAPTER 1 Introduction 1
1.1 MOTIVATION 2
1.2 OVERVIEW 5
1.3 THESIS ORGANIZATION 8
CHAPTER 2 Overall of the Proposed that the
ROI of Rice Planthopper by Image
Processing 9
2.1 IMAGE PREPROCESSING AND SET ROI 12
2.1.1. Image preprocessing 12
2.1.2. Set ROI 14
2.2 COLOR ANALYSIS AND CLASSIFICATION 17
2.2.1. Color analysis 17
2.2.2. Classification 20
2.3 ADD NIR IMAGE TO CLASSIFY 20
2.4 MARK RPHS 24
CHAPTER 3 Experimental Results 28
CHAPTER 4 Conclusion 41
CHAPTER 5 Acknowledgment 43
REFERENCES 45

參考文獻

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指導教授

蔡宗漢(Tsung-Han Tsai)

審核日期

2017-8-15

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