Image matching plays a key role in automatic DTM generation and house extraction. For the house extraction from large scale imagery, point matching and line matching complement one another: Line matching gives the 3 dimensional line information which supports house reconstruction at ridge lines or roof boundaries; dense well distributed point matching results contribute to the surface model generation of the remaining non-breakline regions. We propose a new epipolar line equation, which is determined by orientation parameters and supports both epipolar line search and epipolar imagery generation. The proposed matching process is divided into point matching and line matching. To derive highly reliable results in point matching we include blunder suppression based on the positional relationship between possible corresponding point pairs. Line matching is supported by the results of point matching to reduce the number of possible corresponding line pairs. Regarding similarity comparison for line matching we use the line shape, the flanking regions colour, information on positional relationship and connectivity between candidates for corresponding lines and neighbouring points and lines. We tested the proposed method with a sample dataset and show the results .
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