Ear biometrics has been found to be a good and reliable technique for human recognition. With the initial doubts on
uniqueness of the ear, ear biometrics could not attract much attention. But after it has been said that it is almost impossible
to find two ears with all the parts identical, ear biometrics has gained its pace. To automate the ear based recognition
process, ear in the image is required to be localized automatically. This paper presents a technique for the same. Ear
localization in the proposed technique is carried out by using the hierarchical clustering of the edges obtained from the
side face image. The technique is tested on a database consisting of 500 side face images of human faces collected at IIT
Kanpur. It is found to be giving 94.6% accuracy.
In this paper we consider the issues involved in the 3D mapping of object surface temperatures from a system of thermal and normal stereo cameras. Of particular focus are issues related to integrated thermal and stereo camera calibration using a common visible and thermal calibration grid and the development of robust 3D thermal mapping algorithms that allow for seamless surface temperature calculations. Finally we have examined the class of objects that this system can robustly apply to as well as pinpoint deficiencies in such approaches to 3D surface temperature calculations from thermal cameras.