A detailed evaluation of colour representations for image recognition

Balamurugan, Senthilnathan (2023) A detailed evaluation of colour representations for image recognition. Masters thesis, Dublin, National College of Ireland.

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Abstract

The investigation of colour channels as a key element impacting classification accuracy has drawn a lot of attention in the field of image classification. The encoding of colour information in images, which is essential for communicating visual content, is a critical part of image recognition. This study offers a thorough and methodical assessment of different color representations for image recognition tasks. Through a methodical investigation of numerous colour modes, including RGB, grayscale, and individual colour channels, the study discovers broad results with value for both academic and practical applications.The model using only the Red and Green colour channels is found to be the most successful in reliably differentiating between awake and drowsy states in a thorough review of drowsiness detection methods. This amazing discovery challenges popular opinion and highlights how effective some colour modes are in improving accuracy. The results of this study provide substantial insight on the advantages and disadvantages of various color representations for image classification tasks.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Estrada, Giovani UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence > Computer vision Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence > Computer vision
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	08 Nov 2024 12:14
Last Modified:	08 Nov 2024 12:14
URI:	https://norma.ncirl.ie/id/eprint/7170

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