Line and Word Matching in Old Documents

This paper is concerned with the problem of establishing an index based on word matching. It is assumed that the book was digitised as better as possible and some pre-processing techniques were already applied as line orientation correction and some noise removal. However two main factor are responsible for being not possible to apply ordinary optical character recognition techniques (OCR): the presence of antique fonts and the degraded state of many characters due to unrecoverable original time degradation. In this paper we make a short introduction to word segmentation that involves finding the lines that characterise a word. After we discuss different approaches for word matching and how they can be combined to obtain an ordered list for candidate words for the matching. This discussion will be illustrated by examples.

Clustering Techniques for Marbles Classification

Automatic marbles classification based on their visual appearance is an important industrial issue. However, there is no definitive solution to the problem mainly due to the presence of randomly distributed high number of different colours and its subjective evaluation by the human expert. In this paper we present a study of segmentation techniques, we evaluate they overall performance using a training set and standard quality measures and finally we apply different clustering techniques to automatically classify the marbles. KEYWORDS: Segmentation, Clustering, Quadtrees, Learning Vector Quantization (LVQ), Simulated Annealing (SA).