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研究生:游仁宏
研究生(外文):YU, JEN-HUNG
論文名稱:基於最佳化直方圖實現嵌入式水草生長控制系統
論文名稱(外文):Realization of Embedded Aquarium Plants Growth Control System Based on Optimized Histogram
指導教授:許佳興許佳興引用關係
指導教授(外文):SHEU, JIA-SHING
口試委員:李俊賢何健鵬
口試委員(外文):LEE, JIN-SHYANHO, CHIEN-PENG
口試日期:2020-07-08
學位類別:碩士
校院名稱:國立臺北教育大學
系所名稱:資訊科學系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:70
中文關鍵詞:樹莓派嵌入式系統水草輪廓偵測影像處理
外文關鍵詞:Raspberry PiEmbedded systemAquatic plantFeature detectionComputer vision
DOI:10.6344/THE.NTUE.CS.027.2020.B02
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本研究目的在於使用樹莓派嵌入式平台連接感測裝置,包含網路攝影機、繼電器及溫度感測器建置完成。定期對水草缸拍攝照片,經由程式分析判斷目前環境是否為水草生長之適當條件,再透過樹莓派連接繼電器控制設備開關營造適合水草生長環境,減少人們日常照顧、維護的工作,使培養水草更便利,將省下的時間花在欣賞水草上。
在過去的研究中為達到水草自動化生長控制,以電晶體微控制器及降壓轉換等電子元件為實驗平台,達到最佳化控制燈光與二氧化碳供應。本研究藉由網路攝影機取得靜態影像,透過影像的變化監控水草生長狀況,透過雜訊過濾、彩色直方圖變化、特徵輪廓變化等數據,自動控制調整環境。

This thesis implements an automated appliance based on embedded system Raspberry Pi which is connected to relays, webcam and water-proof temperature sensor for optimized aquatic plant cultivation solution. Collecting the photo of aquatic plant via camera regularly, analyze whether the current condition is suitable for the aquatic plant. It can reduce the daily care and maintenance of aquatic plants. Make it easier to cultivate aquatic plants. Spend the time saved on admiring water plants.
The earlier study was of cultivate aquatic plant by implied transistors and microchip circuits to control light and CO2 supplied for optimized automated aquatic plants. In this experiment, a low-cost embedded platform Raspberry Pi and basic device are introduced. With images showing the changes of aquatic plant, processed by noise reduction, color histogram and edge feature detection, system could automatically adjust the amount of lights and CO2 supplied for construct a comfort environment for plant.

摘要 i
Abstract ii
目錄 iii
表目錄 v
圖目錄 vi
第一章 緒論 1
1.1 前言 1
1.2 動機與目的 2
1.3 問題陳述 4
1.4 方法與貢獻 5
1.5 論文架構 6
第二章 文獻回顧與相關技術 7
2.1 水生植物(Aquatic Plant) 7
2.2 水族造景(Aquascaping) 10
2.3 藻類(Algae) 15
2.4 電腦視覺技術(Computer Vision) 17
2.5 Canny邊緣偵測(Canny Edge Detecting) 19
2.6 RGB及HSV色彩空間 22
2.7 RGB轉換HSV 24
第三章 研究設計與方法 25
3.1 樹莓派(Raspberry pi) 25
3.2 系統架構 30
3.3 水草 33
3.4 水草缸 34
3.5 影像處理 39
3.6 影像直方圖(Image histogram) 41
第四章 實驗設計及結果 50
4.1 RGB色彩空間分析 50
4.2 HSV色彩空間分析 54
4.3 目標輪廓偵測分析 61
第五章 結論與未來展望 65
5.1 結論 65
5.2 未來展望 65
參考文獻 66


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