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CBIR-Two novel contributions to Content Based Image Retrieval are presented and
discussed. The fi rst is a search engine for font recognition. The intended usage
is the search in very large font databases. The input to the search engine is an
image of a text line, and the output is the name of the font used when printing
the text. After pre-processing and segmentation of the input image, a local
approach is used, where features are calculated for individual characters. The
method is based on eigenimages calculated from edge fi ltered character images,
which enables compact feature vectors that can be computed rapidly. A system
for visualizing the entire font database is also proposed. Applying geometry
preserving linear- and non-linear manifold learning methods, the structure of
the high-dimensional feature space is mapped to a two-dimensional representatn,which can be reorganized into a grid-based display.
discussed. The fi rst is a search engine for font recognition. The intended usage
is the search in very large font databases. The input to the search engine is an
image of a text line, and the output is the name of the font used when printing
the text. After pre-processing and segmentation of the input image, a local
approach is used, where features are calculated for individual characters. The
method is based on eigenimages calculated from edge fi ltered character images,
which enables compact feature vectors that can be computed rapidly. A system
for visualizing the entire font database is also proposed. Applying geometry
preserving linear- and non-linear manifold learning methods, the structure of
the high-dimensional feature space is mapped to a two-dimensional representatn,which can be reorganized into a grid-based display.
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