Abstract
The problem of scene matching is a challenging problem in the field of image processing and pattern recognition. Therefore, it is modeled and its influencing factors are analyzed. According to sources, influence factors can be catalogued into three types: 1- changes of scenes 2- changes of image conditions 3- changes of sensors. For each factor, its mechanism is discussed. Given a pictorial description of a region of a scene, it is desired to determine which region in another scene is similar. The most efficient algorithms for scene matching are discussed. Those are the sequential hierarchical scenes matching algorithms for grey-scale and binary images and the two-stage template-matching algorithm. Experimental results are presented for matching satellite images of AI-Minea (EGYPT) and Montana (USA) using those approaches. The results prove efficiency and success in reaching the best match location with minimum required computations. A comment on the results is presented as well as a comparison between the applied methods.
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