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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. IRC, Universiti Teknologi PETRONAS. (Submitted)

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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
Academic Subject : Academic Department - Information Communication Technology
Subject: Q Science > Q Science (General)
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: 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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