A Study for Adaptation of Image Stitching to Big Data Frameworks

In this study, we adopt image stitching process to bigdata frameworks. To do so, an
algorithm is presented to merge two large images in accordance with Hadoop’s map/reduce
computation paradigm. Images are first converted to bitmaps which are represented as matrices
of 0s and 1s. The algorithm then finds the best possible match among two matrices by trying
all possible overlapping situations. The main aim of the study is improving the performance
and scalability of image stitching processes by using a bigdata framework based on map/reduce
distributed computation paradigm.


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