Thermal Human face recognition based on Haar wavelet transform and series matching technique
Ayan Seal, Suranjan Ganguly, Debotosh Bhattacharjee, Mita Nasipuri,, Dipak kr. Basu

TL;DR
This paper presents an efficient thermal IR face recognition method using Haar wavelet transform to extract features from temperature-based images, achieving up to 95% accuracy.
Contribution
It introduces a novel approach combining Haar wavelet transform and series matching for thermal face recognition, focusing on low-frequency features for improved accuracy.
Findings
Achieved up to 95% recognition accuracy.
Effective extraction of temperature-based facial features.
Validated on laboratory and public IR face image datasets.
Abstract
Thermal infrared (IR) images represent the heat patterns emitted from hot object and they do not consider the energies reflected from an object. Objects living or non-living emit different amounts of IR energy according to their body temperature and characteristics. Humans are homoeothermic and hence capable of maintaining constant temperature under different surrounding temperature. Face recognition from thermal (IR) images should focus on changes of temperature on facial blood vessels. These temperature changes can be regarded as texture features of images and wavelet transform is a very good tool to analyze multi-scale and multi-directional texture. Wavelet transform is also used for image dimensionality reduction, by removing redundancies and preserving original features of the image. The sizes of the facial images are normally large. So, the wavelet transform is used before image…
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Taxonomy
TopicsInfrared Thermography in Medicine · Face and Expression Recognition
