Open Access Semi-annual

InfoTech Spectrum: Iraqi Journal of Data Science

· eISSN 3007-5467 · DOI 10.51173/ijds
Sign in Create account Submit
Article Abstract How to Cite Metrics
View PDF
Research article Open Access EN pp. 27–39 · 30 Jan 2025

Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50

  1. College of Health and Medical Techniques, Middle Technical University, Baghdad, Iraq
✱ Corresponding author: [email protected]
DOI 10.51173/ijds.v2i1.66 IJDS-TRK-2026-66 2 views 0 downloads

Abstract

Detecting smoke that precedes fire is a vital matter since it will detect fire incidents in a very early stage since these incidents have very high catastrophic effects on people's lives as well as industrial matters. In order to produce a more reliable detection system, in this article, we dove deeper to examine the effect of colour conversion of the captured footage to enhance the detection percentage using a pre-trained CNN model (ResNet50) that was altered to do a binary classification and was trained on a dataset that consists of smoke and non-smoke scenario images. We examined the system using the footage's original status (RGB) and also tested four colour spaces (HSV, YCbCr, LAB, and grayscale). The testing results showed that HSV had the highest accuracy of 92.1% and the lowest errors during training and testing. Regarding accuracy, the order after HSV was RGB, YCbCr, LAB, and finally, grayscale. Grayscale was the lowest in the testing results, with 85.4%. These results indicate that colour spaces do affect the detection quality and using them would improve the quality of smoke detection systems.
Keywords
Transformation (genetics) Space (punctuation) Artificial intelligence Pattern recognition (psychology) Computer science Remote sensing Geography Biology

Usage Statistics

Nov 2025 → Oct 2026

0

Total Downloads

2

Total Views

How to cite

Mohannad Taha and Mohamed Safaa. 2025. Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50. InfoTech Spectrum: Iraqi Journal of Data Science 2, 1 (2025), 27–39. https://doi.org/10.51173/ijds.v2i1.66

Taha, M. ; Safaa, M.. Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50. InfoTech Spectrum: Iraqi Journal of Data Science 2025, 2 (1), 27–39. https://doi.org/10.51173/ijds.v2i1.66

Taha, M. & Safaa, M. (2025). Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50. InfoTech Spectrum: Iraqi Journal of Data Science, 2(1), 27–39. https://doi.org/10.51173/ijds.v2i1.66

TAHA, Mohannad ; SAFAA, Mohamed. Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50. InfoTech Spectrum: Iraqi Journal of Data Science, v. 2, n. 1, p. 27–39, 2025. https://doi.org/10.51173/ijds.v2i1.66

Taha, Mohannad and Safaa, Mohamed. 2025. "Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50." InfoTech Spectrum: Iraqi Journal of Data Science 2 (1): 27–39. https://doi.org/10.51173/ijds.v2i1.66

Taha, M. and Safaa, M. (2025) 'Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50', InfoTech Spectrum: Iraqi Journal of Data Science, 2(1), pp. 27–39. https://doi.org/10.51173/ijds.v2i1.66

M. Taha and M. Safaa, "Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50," InfoTech Spectrum: Iraqi Journal of Data Science, vol. 2, no. 1, pp. 27–39, 2025. doi: https://doi.org/10.51173/ijds.v2i1.66.

Taha, Mohannad and Safaa, Mohamed. "Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50." InfoTech Spectrum: Iraqi Journal of Data Science, vol. 2, no. 1, 2025, pp. 27–39. https://doi.org/10.51173/ijds.v2i1.66

Mohannad Taha and Mohamed Safaa. "Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50." InfoTech Spectrum: Iraqi Journal of Data Science 2, no. 1 (2025): 27–39. https://doi.org/10.51173/ijds.v2i1.66

Taha M , Safaa M. Impact of Colour Space Transformation on Smoke Detection Accuracy using RESNET50. InfoTech Spectrum: Iraqi Journal of Data Science. 2025;2(1):27–39. https://doi.org/10.51173/ijds.v2i1.66

Similar Articles