Abstract
In this paper, a multi-level dynamic programming approach is used to solve the line segment based correspondence problem in axial motion stereo. In this method, a Local Similarity Measure is calculated for each line segment pair between the Front and Back images. In level 1, the matching probability between line segments is represented by their Local Similarity Measure (LSM). Line segment pair that have a matching probability larger than a threshold T 1 is selected as potential matching pair. T 1 is set to a relative high value so that the probability of correct match of level 1 is very high. Dynamic programming is then used to search for their best match. Based on the geometric properties between the matched and the unmatched line segments, a Global Similarity Measure (GSM)is calculated for each unmatched line segment pair. An overall Similarity Measure (matching probability) is then obtained by the LSM and the GSM. Then, the algorithm begin the second match but with a slightly lower threshold T 2. The new matched results are then used to modify the GSM and the overall Similarity Measure. These processes are repeated until a predefined level n stop (or a predefined condition) is reached. By using the GSM and multi-level searching technique, the proposed technique increases the matching accuracy and reduce the number of unmatched line segment due to misordering when dynamic programming is used for axial motion stereo matching.
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© 1997 Springer-Verlag Berlin Heidelberg
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Yip, R.K.K. (1997). Multi-level dynamic programming for axial motion stereo line matching. In: Del Bimbo, A. (eds) Image Analysis and Processing. ICIAP 1997. Lecture Notes in Computer Science, vol 1310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63507-6_252
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DOI: https://doi.org/10.1007/3-540-63507-6_252
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