e-recognition of Motorbike License Plate using Python and SQLite
نویسندگان
چکیده
Objectives: (1) To solve the problem of inefficiency and inaccuracy vehicle monitoring; (2) propose develop a software that will serve as initial replacement to man-to-man motorbike (3) Evaluate components system in terms functionality, efficiency, accuracy. Methods: Waterfall model was used development model. The proposal is evaluation. Python 3.6 program coding, Graphical User Interface (GUI) Tkinter, database SQLite, image processing OpenCV utilized. KNN algorithm machine learning technique. Using Slovin’s formula finding sample respondents with 95% confidence level 5 % margin error, resulted 33 respondents. survey questionnaire ISO 9126 Quality Software bases for Frequency distribution, percentage, weighted mean were interpret data gathered from evaluation metrics. Findings: Likert Scale System, efficiency 4.25 described Highly Acceptable, accuracy 4.73 interpreted Acceptable. overall 4.49 acceptable. functionality using percentage frequency distribution 100% functional. solution inefficient inaccurate monitoring. interpretation can be considered recommendation further study additional features advance version license plate recognition. Limitations or non-recognizable pieces found bearable future studies recommended. Novelty: Initial Step replacing License Plate Monitoring. Author ‘s developing inaccurately monitoring status congested number vehicles passing out certain vicinity, specifically motorbikes. Keywords: e-recognition; Motorbike; Man-To-Man Monitoring; Replacement;
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ژورنال
عنوان ژورنال: Indian journal of science and technology
سال: 2022
ISSN: ['0974-5645', '0974-6846']
DOI: https://doi.org/10.17485/ijst/v15i48.1673