NORMALIZED WEIGHTED LEVENSTHEIN DISTANCE AND TRIANGLE INEQUALITY IN THE CONTEXT OF SIMILARITY DISCRIMINATION OF BILEVEL IMAGES

This work shows that the weighted Levensthein distance under normaliza tion satisfies the triangle inequality, not unconditionally, but under the hypothesis of practical occurrence, This characteristic makes the normalized weighted Levensthein distance a good candidate as a string distance for shape similarity discrimination of bilevel images. It is shown that a string distance is ideal for such a role when it is a no rmalized metric.