Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep Learning

Saifbudin, Abdul Syahid (2019) Improving the Accuracy to Count Bottle Caps by Implementation of Computer Vision and Deep Learning. [Final Year Project] (Submitted)

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Abstract

The current system to detect the bottle caps is using the HSV (Hue, Saturation and Value)
technique. This technique has an accuracy of 85.938% to count the bottle caps. The accuracy of
the system to count the bottle caps can be increased by implementing computer vision with deep
learning. The proposed system should be able improve the accuracy to count the bottle caps. The
development of the system is develop using python, computer vision and deep learning. The
output of the result is expected to improve the accuracy for the detection of the bottle cap by 15
percent.

Item Type: Final Year Project
Subjects: Q Science > Q Science (General)
Departments / MOR / COE: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 09 Sep 2021 19:58
Last Modified: 09 Sep 2021 19:58
URI: http://utpedia.utp.edu.my/id/eprint/20879

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