A new framework for subimage analysis - Arslan, Abdullah N. (SN applied sciences, 2019)
We develop new methods for several subimage analysis problems. Images in two dimensions are represented by matrixes (higher dimensional images are represented by higher dimensional arrays). This representation yields efficient algorithms for image search and comparison problems applicable not only to images, but also to array search and comparison in any dimension two or larger. Subimage analysis based on our array-representation has limitations. For example, our methods are not rotation and scale invariant. However, they yield efficient algorithms that have practical applications. Videos and snapshots taken from videos are continuously added to the digital world where they are permanently accessible. From a snapshot, one may want to locate and watch the part of the video that contains this snapshot (e.g. moments in news-footage, soccer or olympic games). One may also want to find common parts (sequences of frames) in multiple videos for various reasons (e.g. copyright-check, false-news detection). Our algorithms are applicable in these cases. For another application, we propose representing RNA secondary structures by matrixes. Since our methods are applicable to submatrix analysis, RNA substructure search and multiple RNA structure comparison problems can be solved by using our algorithms (for exact matches).