The identification of laboratory mice has been an important issue in pharmaceutical applications ever since tests have been performed on animals. As biometric identification has become an increasingly important issue over the past decade, attempts are underway to replace traditional identification methods, which are mostly invasive and limited in code space. This thesis discusses a project that aims at identifying mice by biometrically examining the blood vessel patterns in their ears.

In the proposed algorithm, firstly, the blood vessel structure within the obtained images got enhanced before segmenting the image in blood vessel and non-blood vessel portions. In the next step a sufficient amount of unique feature points got extracted from the segmented image. The obtained feature points were afterwards used for the actual identification procedure.

Out of 20 mice, 18 could be identified successfully using the proposed algorithm.