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Rectification of Illumination on 3D Shape Recovery

Authors: Saeed Muhammad Mannan; Tae-Sun Choi;

Rectification of Illumination on 3D Shape Recovery

Abstract

In the area of machine vision, shadows occur frequently in a wide variety of scenes. An inherent weakness of focus-based methods is that, they require the imaged scene to have significant texture. In many real-world applications, surfaces can be smoothly shaded, lacking detectable texture. In such cases, Shape-Form-Focus (SFF) generates inaccurate and sparse depth maps. For accurate calculation of depth map, we consider the affects of illumination. In SFF, the images are taken with one light source and the shadows occur in each frame. Thus, the more bright regions of the images give more accurate depth map, whereas, the less bright regions give less accurate depth map. We have shown the results and compared them with the previous results. From simulation results, we see that the results are improved with the proposed algorithm.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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