The term morph derives from Greek morphē, which means shape or form. For further research, different software may be used to create morphs as exponential functions. The main limitation encountered in this research is that Abrosoft Fantamorph only permits the creation of morphs as linear functions. Image morphing provides important findings on the changes in our environment while contributes to research agencies as NASA. With the morphs between these two images, we can determine the rate in which the snowpack decreases during the five years. In addition, we compare the snowpack in Sierra Nevada, California images taken in March 2010 and March 2015. In this particular case, we can predict the countries in the world that will be affected at any year of the time frame including the future. The study of the Global Water Crisis is performed creating frames of the map from 1995 to 2025. The continuous water decrease in different lakes is analyzed, where the software re-veals the transition between two time-varying images. This re-search studies the slow changes that occur on various environments along the planet. Abrosoft Fantamorph Deluxe 5.0 software is used in this research to create a series of time- varying frames. In real life, each image has a large number of points and triangles that form the triangulation pattern, and for this reason we use different application software to create image morphs. This procedure represents the basics of morphing calculations using linear algebra parameterization of line segments to determine the path and final location of each point compared to the rest. The morph is ap-plied from triangle to triangle by affine transformations that distort and blend two im-ages. Triangulation of an image is the dis-tribution of those key points along an image creating small triangles. The process to morph a pair of images begins with the selection of key points that transform from one image to the next. Assuming one image is at time t = 0 and the other at t = 1, we can predict what would be the point’s location at any time “t” between them, generating its corresponding triangle pattern and there-fore its image. In other words, we take two time- varying pic-tures and compare them as if positioned one on top of the other. Image morphing is considered an average between two different images or the gradual transition from one image to another. The purpose of this research is to analyze the mathematics behind image morphing and its usage towards environmental changes. This research paper is the re-sult of the work done in this program1.
The team is part of the summer program CCRI associated to NASA. Angulo Nieves, professor of Mathematics at Hostos Community College and the New York City Research Initiative1. This research is conducted in the summer of 2016 and it is supported by several agen-cies, such as the CILES grant of Prof.
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