科研之友
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摘要
This paper investigates reliable automatic high resolution image to map matching using a novel structural linear feature-based matching (SLIM) method. The main components used by this method are the specific patterns as well as the lines and points generated mathematically. These components are produced by extension and intersection of extracted line-segments. Due to the high numbers of extracted line-segments in both image and object space, the number of possible patterns is very high. In order to decrease the search space, the innovative SLIM method is performed in three main phases. In the first phase, using a new weighting procedure, only optimum numbers of high-qualified well-distributed patterns, which are more likely to have any correspondence in object space, are selected. In the second phase, the aim is to find a pair with maximum numbers of conjugate lines. To do so, all the possible patterns in object space are screened for each selected image pattern using four predefined geometric criteria. Simultaneously, the correspondence of the other crossing lines is also determined in the same manner. In third phase, the pair with maximum numbers of matched-lines is selected among all the results of second phase. Additionally, the final-phase is done to increase the amount of correctly matched-lines. The main contribution of this investigation is automatic and correct matching of linear features with no need to any initial information. Additionally, the end-points of the corresponding lines are not necessarily conjugate points. The results show the high potential of the proposed method in terms of accuracy, reliability, automation, and time reduction even in images with repetitive patterns or a high numbers of outliers.
- 出版日期2016-5
