ESR3 – Dipanjana Saha

Dipanjana Saha

Country of Origin: India
Host Institution: CNAM

Background:

Dipanjana completed her Bachelor’s in Science in Electronics from Calcutta University in 2012. Later she pursued Post B.Sc. Bachelor’s in Technology in Optics and Optoelectronics in 2015 and Master’s in technology (also specializing in Optics and Optoelectronics) from Calcutta University in 2017. Her research interests are Optical metrology, microscopy & spectroscopy, biomedical imaging, and digital holography.

Aspirations within projects:

Dipanjana's main aspiration is to identify how the visual system works to differentiate a real object from an artificial one. Throughout this PhD, she will acquire profound knowledge in 3D printing technology, from acquisition of the shape and the appearance of an object to the print of that object, passing by the compression algorithm, the gestion of the workflow, quality control and measturement after the production. She wants to harness her training on optics to add a new dimension to the metrology field in terms of spatial resolution of measurement.

She wants to build up micro-goniospectrophotometer system to pursue her goal. Along with this she will acquire her personal training on psychophysical experiments to give an integrity to this project.

Apart from her research and academic development, she will develop a network with academic and industrial experts in the field of 3D printing technology, color imaging, optical imaging and of course metrology.

ESR3: Characterization of Natural and Artificial Surfaces using a multiscale approach based on specular BRDF measurement

Main Supervisor:

Co-Supervisor(s):

Objectives

The appearance of an object comes from its visual attributes, which are color, gloss, translucency and texture. These attributes are accessed by measuring the optical properties of the surface and by evaluating the interaction between light and human visual system. To characterize the optical properties, the relevant quantity is the Bi-directional Reflectance Distribution Function (BRDF), that contains values of reflectance for all directions of illumination and all directions of observation. The BRDF is measured with a device called a goniospectrophotometer. Interaction between light and human visual system is accessed by visual experiments and psychophysics. Natural surfaces, i.e. wood, wool, stones or leaves, are the result of a complex and chaotic process. If the surface can look smooth at a reading distance, it is never the case at a microscopic distance. On another side, artificial materials come from chemistry and show less complex microstructural roughness. But Human visual system identifies easily the difference between natural and artificial wood surface, or between real and fake flowers. How?

One assumption is that Human can find in the optical signal entering in the eye, embedded information about the roughness and the microstructure of the surface observed. This information is most probably hidden in the specular peak, which is the specific region of the BRDF that is the contains the information on the roughness. In this general frame, objective of my PhD is to identify structural difference between natural and artificial surfaces. To reach this objective, BRDF measurements will be performed on both categories of surfaces, with a focus on the information contained in the specular peak and available at different scale level, ranging from centimeter size to micrometer size (μBRDF).

Following milestone will be followed:

  1. Set up of a new measurement line on the existing goniospectrophotometer of the lab devoted to microBRDF measurements.
  2. Assemble of a collection of samples representatives of natural and artificial surfaces selected according to a literature study, to the available industrial production and from the production coming from the consortium.
  3. Acquisition of the μtopography of the surfaces.
  4. Optical study of the BRDF of natural and artificial samples.
  5. Psychophysical study of natural and artificial samples.
  6. Research of correlation between visual response and optical responses.