An Application of Mobile Device for Cell Counting based on Morphological Image Processing
碩士 === 國立暨南國際大學 === 電機工程學系 === 104 === As technology continues to advance, the need of biological testing such as detection of blood and cancer cells increase as people pay more attention to their health concern. Conventional manual biological testing, cells are counted one by one with eye observati...
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ndltd-TW-103NCNU04420622017-07-09T04:30:15Z http://ndltd.ncl.edu.tw/handle/56893775091431531156 An Application of Mobile Device for Cell Counting based on Morphological Image Processing 運用形態學技術於細胞個數計算之行動裝置應用 Shih-Yuan Chiu 邱詩媛 碩士 國立暨南國際大學 電機工程學系 104 As technology continues to advance, the need of biological testing such as detection of blood and cancer cells increase as people pay more attention to their health concern. Conventional manual biological testing, cells are counted one by one with eye observation of operators, however, the physical and mental conditions of the operators are likely to affect the observation test to be erroneous results. An automated cell counting by computer is a solution to replace manual counting which can reduce the labor cost and have less error-prone results. In this thesis, an automated cell counting system, that combines a Raspberry Pi, Pi camera, μ Handy action microscopy and image processing algorithms, including the processes of image Gaussian blur processing algorithm, OTSU binary image and morphological operations, is implemented to perform the cell counting in a mobile device. With the implemented automatic cell counting system, users can adjust the algorithm in accordance with the properties of cell image to lower the counting error rate. Experimental results show that our system can achieve accuracy higher than 95%. Meng-Lieh Sheu 許孟烈 2016 學位論文 ; thesis 59 zh-TW |
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碩士 === 國立暨南國際大學 === 電機工程學系 === 104 === As technology continues to advance, the need of biological testing such as detection of blood and cancer cells increase as people pay more attention to their health concern. Conventional manual biological testing, cells are counted one by one with eye observation of operators, however, the physical and mental conditions of the operators are likely to affect the observation test to be erroneous results.
An automated cell counting by computer is a solution to replace manual counting which can reduce the labor cost and have less error-prone results. In this thesis, an automated cell counting system, that combines a Raspberry Pi, Pi camera, μ Handy action microscopy and image processing algorithms, including the processes of image Gaussian blur processing algorithm, OTSU binary image and morphological operations, is implemented to perform the cell counting in a mobile device.
With the implemented automatic cell counting system, users can adjust the algorithm in accordance with the properties of cell image to lower the counting error rate. Experimental results show that our system can achieve accuracy higher than 95%.
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author2 |
Meng-Lieh Sheu |
author_facet |
Meng-Lieh Sheu Shih-Yuan Chiu 邱詩媛 |
author |
Shih-Yuan Chiu 邱詩媛 |
spellingShingle |
Shih-Yuan Chiu 邱詩媛 An Application of Mobile Device for Cell Counting based on Morphological Image Processing |
author_sort |
Shih-Yuan Chiu |
title |
An Application of Mobile Device for Cell Counting based on Morphological Image Processing |
title_short |
An Application of Mobile Device for Cell Counting based on Morphological Image Processing |
title_full |
An Application of Mobile Device for Cell Counting based on Morphological Image Processing |
title_fullStr |
An Application of Mobile Device for Cell Counting based on Morphological Image Processing |
title_full_unstemmed |
An Application of Mobile Device for Cell Counting based on Morphological Image Processing |
title_sort |
application of mobile device for cell counting based on morphological image processing |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/56893775091431531156 |
work_keys_str_mv |
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