臺灣博碩士論文加值系統

本研究的目的在發展一個手機應用程式，利用手機拍照，自動計算照片中的菌落總數與區分類別，取代人工計數，效率低落且費時之問題。市面上雖有自動計算菌落之儀器，但使用條件限制繁多。目前手機與平板裝置已是廣泛普及的工具，如何開發一套自動計算與區分菌落App 程式，讓研究人員可以隨時利用隨身的手持裝置拍攝菌落照片，無需設定參數，即自動辨識照片中菌落種類數並且計算出各種類分別的菌落數與總和，是本研究的最終目標。
本研究的研究議題涵蓋兩大部分，第一部分在區分影像中的前景(菌落)與背
景(培養基及其他)。針對手持裝置的攝影結果中可能存在的各種雜訊，提出解決方案。使用影像分割的局部偵測方式，以及顏色特性來區分前景與背景。第二個部分是自動區分菌落種類以及計算各類的菌落數。在此方法中，我們在CIELAB色彩空間中針對第一部分所篩選出的前景，利用K-means 分群法區分菌落，並對每群菌落建立特徵，再針對剩下未確定的區域，找出可能忽略的菌落，最後計算出菌落總個數與類別。
本研究的成果包含建立兩組效能比較資料集以及一個系統化的比較工具，第一組資料集共33 張，為使用手機拍攝的菌落照片，雜訊較多，第二組資料集共49 張，為OpenCFU 提供的開放資料，無雜訊。兩個資料集均包含一個菌落及多種菌落。本研究所發方法效能，(1)菌落偵測能力，於第一組資料集的表現，平均F 度量值可達到71.6%，在第二組資料集的表現，平均F 度量值達到91.7%，整體平均F 度量值達83.6%左右；(2)多種菌落分群能力，平均F 度量值達91.5%，平均芮氏指標達92.6%。無論(1)或(2)，相對於現有之相關研究或工具(Colony Counter v1.0、OpenCFU、CFU Scope)，實驗數據都顯示本研究的方法為最優。

The purpose of this study is to develop a mobile app that can automatically count and classify multiple bacteria colonies to solve the low efficiency and time consuming manual counting problems. Although there are many automatic colony counting instruments, they suffered from many limitations. Currently, mobile devices are widely spread. Therefore, the goal is to develop an mobile app which can automatically count and classify colonies. The user can take the photos and use the app to identify colonies for summing up the total number without setting any parameter.
This study includes two parts, the first part is to distinguish foreground (colonies) and background (agar and others). We propose methods for isolate the noise from photographs taken by handheld device. A small region (region of interest) detection method and the color characteristics are used in proposed approach to distinguish foreground and background. The second part is to automatically classify different colony types and count total number of colonies in each types. To classify the colonies in the foreground image extracted in first part, we use the values of CIELAB color space of the image as the features, and use K-means clustering algorithm to classify these images. Furthermore, we establish the colony characteristic model for each type of colonies to rescan the uncertain areas, and sums up to the total number for every colony.
In this study, we established two groups of dataset for efficacy comparison and a systematical comparison tool. The first dataset group includes 33 pictures that taken by handheld devices with many noises. The second dataset group includes 49 pictures obtained from OpenCFU open dataset with no noise. Both of the two datasets include single colony species and multiple colony species. The proposed approach achieved the followings: (1) the average F-measure of colony detection can achieve 71.6% in the first dataset, 91.7% in the second dataset and results to the overall accuracy 83.6%, (2) the average F-measure of multiple colony classification can achieve 91.5% and the average rand index (RI) values reaches 92.6%. Compare to the existing studies or tools (Colony Counter v1.0, OpenCFU, CFU Scope), the proposed approach performs the best.

口試委員會審定書 ........................................................................................................... #
誌謝 ................................................................................................................................... i
中文摘要 .......................................................................................................................... ii
ABSTRACT .................................................................................................................... iii
目錄 ................................................................................................................................. iv
圖目錄 ............................................................................................................................ vii
表目錄 ............................................................................................................................... x
Chapter 1 緒論............................................................................................................ 1
1.1 研究背景 ........................................................................................................ 1
1.2 研究動機 ........................................................................................................ 2
1.3 研究目標 ........................................................................................................ 3
1.4 研究貢獻 ........................................................................................................ 4
1.5 論文架構 ........................................................................................................ 5
Chapter 2 文獻探討.................................................................................................... 6
2.1 相關研究 ........................................................................................................ 6
2.2 影像切割 ........................................................................................................ 7
2.2.1 Threshold Segmentation ........................................................................ 7
2.2.2 分水嶺演算法 ....................................................................................... 9
2.3 特徵選取 ........................................................................................................ 9
2.3.1 CIEL*a*b* 色彩空間 .......................................................................... 9
2.3.2 形狀特徵 ............................................................................................. 11
2.4 分 群方法 ...................................................................................................... 12
2.4.1 K-means Clustering ............................................................................. 12
2.4.2 主成份分析 (Principal component analysis) ..................................... 14
2.5 評估分群效果方法 ...................................................................................... 14
Chapter 3 ............................................................................. 17
3.1 問題定義 ...................................................................................................... 17
3.2 原始影像輸入 .............................................................................................. 18
3.3 分離前景與背景 .......................................................................................... 20
3.3.1 掃描影像 ............................................................................................. 21
3.3.2 刪除背景方法 ..................................................................................... 22
3.4 菌落特徵模型建立 ...................................................................................... 27
3.4.1 自動計算分群數並使用K-means 分群 ............................................ 30
3.5 菌落比對 ...................................................................................................... 32
3.6 菌落計數 ...................................................................................................... 32
Chapter 4 實驗結果與討論 ..................................................................................... 35
4.1 菌落偵測實驗 .............................................................................................. 35
4.1.1 實驗影像 ............................................................................................. 35
4.1.2 實驗評估工具 ..................................................................................... 36
4.1.3 實驗結果與討論 ................................................................................. 38
4.2 菌落分群實驗 .............................................................................................. 42
4.2.1 實驗影像 ............................................................................................. 42
4.2.2 多種菌落分群評估方法 ..................................................................... 42
4.2.3 實驗結果與討論 ................................................................................. 43
Chapter 5 結論與未來展望 ..................................................................................... 45
5.1 結論 .............................................................................................................. 45
5.2 未來展望 ...................................................................................................... 46
參考文獻 ......................................................................................................................... 47
附錄A ............................................................................................................................. 50
附錄B ............................................................................................................................. 52
附錄C ............................................................................................................................. 58
附錄D ............................................................................................................................. 64

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