Abstract: During welding or flame cutting of metals, the
prediction of heat affected zone (HAZ) is critical. There is need to
develop a simple mathematical model to calculate the temperature
variation in HAZ and derivative analysis can be used for this purpose.
This study presents analytical solution for heat transfer through
conduction in mild steel plate. The homogeneous and nonhomogeneous
boundary conditions are single variables. The full field
analytical solutions of temperature measurement, subjected to local
heating source, are derived first by method of separation of variables
followed with the experimental visualization using infrared imaging.
Based on the present work, it is suggested that appropriate heat input
characteristics controls the temperature distribution in and around
HAZ.
Abstract: In this work we present an efficient approach for face
recognition in the infrared spectrum. In the proposed approach
physiological features are extracted from thermal images in order to
build a unique thermal faceprint. Then, a distance transform is used
to get an invariant representation for face recognition. The obtained
physiological features are related to the distribution of blood vessels
under the face skin. This blood network is unique to each individual
and can be used in infrared face recognition. The obtained results are
promising and show the effectiveness of the proposed scheme.
Abstract: Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.