The use of arch index to characterize arch height: a digital image processing approach

1995 ◽  
Vol 42 (11) ◽  
pp. 1088-1093 ◽  
Author(s):  
Woei Chyn Chu ◽  
Shin Hwa Lee ◽  
W. Chu ◽  
Tzyy-Jiuan Wang ◽  
Maw-Chang Lee
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Arch Height ◽  
Processing Approach ◽  
Arch Index

scholarly journals Mobile Screening Framework of Anterior Segment Photographed Images

2018 ◽  
Vol 7 (4.11) ◽  
pp. 85
Author(s):  
N Syahira M Zamani ◽  
Laily Azyan Ramlan ◽  
W Mimi Diyana W Zaki ◽  
Aini Hussain ◽  
Haliza Abdul Mutalib
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Anterior Segment ◽  
Qualitative Assessment ◽  
Computational Time ◽  
Future Studies ◽  
Processing Approach ◽  
Processing Platform ◽  
Mobile Screening

This work presents a qualitative measurement of anterior segment photographed images (ASPIs) to identify between normal eyes and eyes with pterygium and pinguecula through Otsu multi-thresholding approach without contrast enhancement. In addition, we also propose a mobile screening framework of ASPIs through smartphones. ASPIs were directly sent to the cloud storage once an ASPI was captured using a smartphone camera, and then each image was processed through a digital image processing approach in a processing platform. Three important steps, namely, pre-processing, image segmentation and qualitative assessment, are involved in the processing platform of the mobile screening framework. The ASPIs are pre-processed to minimise or eliminate any unwanted areas within the image. Then, these ASPIs are segmented through multi-thresholding Otsu approach with clustering number n = 3. Segmentation result shows that the accuracy of the proposed method is 87.5%, which is comparable with the previously established work that has applied three-step differencing (3SD) method. However, the proposed approach has better computational time which is six times faster than the 3SD method. These results demonstrate a remarkable effort to produce a simple but straightforward digital image processing approach to be implemented in cloud computing for future studies.                                                                                       

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