Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/100605
Title: 2D image deformation based on guaranteed feature correspondence and mesh mapping
Authors: Liu, Yaqiong
Lin, Xin
Shou, Guochu
Seah, Hock Soon
Keywords: DRNTU::Engineering::Computer science and engineering
Automatic Contour Exaction
2D Image Deformation/Morphing
Issue Date: 2018
Source: Liu, Y., Lin, X., Shou, G., & Seah, H. S. (2019). 2D image deformation based on guaranteed feature correspondence and mesh mapping. IEEE Access, 7, 5208-5221. doi:10.1109/ACCESS.2018.2887078
Series/Report no.: IEEE Access
Abstract: Image deformation has ubiquitous usage in multimedia applications. It morphs one image into another through a seamless transition. Existing techniques either mainly focus on the correspondence mapping of interior features of the objects in two images, without considering object contours, or sketch contours manually, resulting in tedious work for users. Thus, we propose a 2D image deformation method, which extracts object contours automatically, considers both inner features and contours as constraints and preserves image features in terms of visual importance. Our method first automatically extracts the object contours in the source and target images and then allows users to sketch some interior features in both the images. Then, our method tessellates two images to generate two triangular meshes and builds a guaranteed bijective mesh mapping between them. We also prove the bijectivity of our mesh mapping and discuss its other desirable properties. Then, our method generates the intermediate images between the source and target images by calculating the intermediate meshes and pixels of each intermediate image. Our method realizes automatic contour extraction, provides an intuitive user interface and utilizes harmonic maps to establish a bijective mesh mapping. Therefore, it preserves more significant features with less distortion and works well for many image deformation cases in real time.
URI: https://hdl.handle.net/10356/100605
http://hdl.handle.net/10220/48565
DOI: 10.1109/ACCESS.2018.2887078
Rights: © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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