dc.creator |
Nombo, Josiah |
|
dc.creator |
Mwambela, Alfred |
|
dc.creator |
Kisangiri, Michael |
|
dc.date |
2016-05-19T13:07:34Z |
|
dc.date |
2016-05-19T13:07:34Z |
|
dc.date |
2015 |
|
dc.date.accessioned |
2018-03-27T08:52:55Z |
|
dc.date.available |
2018-03-27T08:52:55Z |
|
dc.identifier |
Nombo, J., Mwambela, A. and Kisangiri, M., 2015. Performance Analysis of Grey Level Fitting Mechanism based Gompertz Function for Image Reconstruction Algorithms in Electrical Capacitance Tomography Measurement System. International Journal of Computer Applications, 109(15). |
|
dc.identifier |
http://hdl.handle.net/20.500.11810/2154 |
|
dc.identifier |
10.5120/19263-0960 |
|
dc.identifier.uri |
http://hdl.handle.net/20.500.11810/2154 |
|
dc.description |
This paper analyses the performance of grey level fitting
mechanism based on Gompertz function used in Electrical
Capacitance Tomography measurement system. In order to
evaluate its performance, the data fitting mechanism has been
applied to common image reconstruction algorithms which
include; Linear Back Projection, Singular Value
Decomposition, Tikhonov Regularization, Iterative Tikhonov
Regularization, Landweber iteration and Projected Landweber
iteration. Images were reconstructed using measured
capacitance data for annular and stratified flows, and
qualitative and quantitative evaluation were done on the
reconstructed images in comparison with respective reference
images. Results show that this grey level fitting mechanism is
better in terms of improving image spatial resolution,
minimizing relative image error and distribution error and
maximizing correlation coefficient. |
|
dc.language |
en |
|
dc.subject |
Electrical capacitance tomography |
|
dc.subject |
Image reconstruction algorithms |
|
dc.subject |
Data fitting |
|
dc.subject |
Gompertz function |
|
dc.title |
Performance Analysis of Grey Level Fitting Mechanism based Gompertz Function for Image Reconstruction Algorithms in Electrical Capacitance Tomography Measurement System |
|
dc.type |
Journal Article, Peer Reviewed |
|