Informatica

This study uses the r-theta transformation technique to map a fingerprint image to the straight-line signals. Subsequently, the “vector magnitude invariant transform” technique is applied to them to generate an invariant magnitude for person identification. This technique can solve the image rotation problem. Various vertical magnitude strips are generated to deal with the image-shifting problem. The algorithm developed in this study can precisely classify the fingerprint images.

This study uses object-extracting technique to extract – thumb, index, middle, ring, and small fingers from hands. The algorithm developed in this study can find precise locations of fingertips and finger-to-finger-valleys. The extracted fingers contain many useful geometry features. One can use these features to conduct the person identification. Geometry descriptor is used to transfer geometry features of fingers to another feature-domain for image-comparison. Image subtraction is used to exam difference of two fingers. This study uses the fingers as features to recognize different persons.