| dc.creator |
Rweshobora, Kelvin Christopher |
|
| dc.date |
2018-08-17T12:20:23Z |
|
| dc.date |
2018-08-17T12:20:23Z |
|
| dc.date |
2017 |
|
| dc.date.accessioned |
2022-10-20T13:46:53Z |
|
| dc.date.available |
2022-10-20T13:46:53Z |
|
| dc.identifier |
Rweshobora, K. C. (2017). Using number recognition techniques to automate the revenue collection at mini bus terminals: a case of Dodoma municipal. Dodoma: The University of Dodoma |
|
| dc.identifier |
http://hdl.handle.net/20.500.12661/448 |
|
| dc.identifier.uri |
http://hdl.handle.net/20.500.12661/448 |
|
| dc.description |
Dissertation (MSc Information Technology) |
|
| dc.description |
The Number Recognition (NR), is a modern technique that uses optical character recognition on images to obtain desired characters. The technique involves four steps Image acquisition, preprocessing, character segmentation and Character recognition. This technique has been used in activities like license plate detection as Automatic Number Plate Recognition (ANPR). The manual revenue collection process currently operating at the Dodoma Municipal mini bus terminals has deprived the Local Government Authority (LGA) of its potential income. This research attempts solve this problem by automating the current revenue collection process at the mini bus terminals in Dodoma Municipal by using, Number recognition techniques and OCR.
The research has adopted a case study research design and simulation in the problem investigation and proposed simulation development respectively. The research has used key informant interviews and observations to acquire a good understanding of the current operations at the mini bus terminals and the necessary requirements to achieve the main goal of the study.
Simulation of the Number Recognition System (NRS) was achieved by using Matlab R2017a as a simulation tool on a Dell computer running windows 7 professional, Hard Disk Drive (HDD) 500 Gigabyte (GB), Random Access Memory (RAM) 4 Gigabyte. The research, achieved a simulation for NRS with an accuracy of 0.988 for the character recognition of the captured Surface and Marine Transport Regulatory Authority (SUMATRA) numbers on mini buses. The researcher recommends a further study on the image acquisition process and messaging alert system, 2to completely automate the process. |
|
| dc.language |
en |
|
| dc.publisher |
The University of Dodoma |
|
| dc.subject |
Automatic Number Plate Recognition |
|
| dc.subject |
Dodoma |
|
| dc.subject |
Local Government Authority |
|
| dc.subject |
Tanzania |
|
| dc.subject |
Messaging alert system |
|
| dc.subject |
Income |
|
| dc.subject |
Revenue |
|
| dc.subject |
Optical character recognition |
|
| dc.subject |
Character segmentation |
|
| dc.subject |
Image acquisition process |
|
| dc.subject |
Simulation |
|
| dc.subject |
Character recognition |
|
| dc.subject |
Number recognition |
|
| dc.subject |
Revenue collection |
|
| dc.subject |
Taxation |
|
| dc.title |
Using number recognition techniques to automate the revenue collection at mini bus terminals: a case of Dodoma municipal |
|
| dc.type |
Dissertation |
|