“Measuring Microstructures Using Confocal Laser Scanning Microscopy for Estimating Surface Roughness” by Dobashi, Ijiri, Todo, Iwasaki, Okabe, et al. …
Conference:
Type(s):
Entry Number: 72
Title:
- Measuring Microstructures Using Confocal Laser Scanning Microscopy for Estimating Surface Roughness
Presenter(s)/Author(s):
Abstract:
Realistic image synthesis is an important research goal in computer graphics. One important factor to achieve this goal is a bidirectional reflectance distribution function (BRDF) that mainly governs an appearance of an object. Many BRDF models have therefore been developed. A physically-based BRDF based on microfacet theory [Cook and Torrance 1982] is widely used in many applications since it can produce highly realistic images. The microfacetbased BRDF consists of three terms; a Fresnel, a normal distribution, and a geometric functions. There are many analytical and approximate models for each of these terms.
Our ultimate goal of this research project is to find an accurate and analytical expression of BRDFs for rendering different foods by measuring their microstructures using microscopic imaging devices. Although there have been many researches on measuring BRDFs,they basically measure reflected light with different lighting and viewing directions. We instead measure the microstructures and construct microfacet-based BRDFs from the measurements. We begin with estimation of surface roughness, which is presented in this poster.
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Additional Images:
![©Yoshinori Dobashi, Takashi Ijiri, Hideki Todo, Kei Iwasaki, Makoto Okabe, and Satoshi Nishimura](https://history.siggraph.org/wp-content/uploads/2022/10/2016-Poster-72-Dobashi_Measuring-Microstructures-Using-Confocal-Laser-Scanning-Microscopy-for-Estimating-Surface-Roughness-04.jpg)
![©Yoshinori Dobashi, Takashi Ijiri, Hideki Todo, Kei Iwasaki, Makoto Okabe, and Satoshi Nishimura](https://history.siggraph.org/wp-content/uploads/2022/10/2016-Poster-72-Dobashi_Measuring-Microstructures-Using-Confocal-Laser-Scanning-Microscopy-for-Estimating-Surface-Roughness-05.jpg)
Acknowledgements:
This work was supported by JSPS KAKENHI Grant Number JP15H05924.