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Urine test strip analysis using image processing for mobile application
Ira Valenzuela1, Timothy Amado2, John William Orillo3.
In attaining vital information for diagnostic purposes in medicine, analysis of the urine
sample or urinalysis is a powerful tool. Urine test strip is commonly used in this kind of
assessment. In this study, a mobile application has been developed for urine test strip
analysis using image processing. Glucose, pH, specific gravity and protein levels are
determined and analyzed by the system. The urine test strip is captured using an
Android phone, and then the image captured is analyzed using the algorithm
employed in OpenCV. Harris detection and RANSAC algorithms are utilized to provide
an accurate homography estimation. A portable document format report has been
generated to provide the summary of analysis. One-hundred seventy-one (171) urine
test strips images are stored in the SQLite database of the mobile phone. And 54 urine
samples are tested for the accuracy of the system. The study showed that the overall
accuracy is 91.7%.
Affiliation:
- Technological University of the Philippines, Philippines
- Technological University of the Philippines, Philippines
- Technological University of the Philippines, Philippines
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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