Psycho-physical assessment of differences between color Gaussian distributions

Considering the design and fabrication of new material surfaces having a natural or complex aspect (wood, granite, leather…), it is a challenge to visually reproduce the same color aspect. To avoid any confusion, we are interested in texture perceived by human, also known as non-uniform and homogeneous aspect [1]. The question of this project is: How can we measure the distance between two textures to improve the quality control?

The first objective is to assess the Just Noticeable Difference for non-uniform patches starting from color Gaussian distributions. The second one is to create a distance linked to human perception of nonuniform aspect scaling.

A state of the art of the actual research on Just Noticeable Difference can be seen [2-4].

The purposed timeline for the Ph.D thesis is as follow :

• Task 1 : Develop an experimental protocol to evaluate the JND between two nonuniform surfaces. Realize the psycho-visual experiment associated to the protocol. Analyze the data from experiments to determine a JND depending on the variations of the 3D Gaussian non-uniform surfaces.
• Task 2 : Develop an experimental protocol to evaluate order and scale of human perception of nonuniform aspect. Realize the psychophysical experiment associated to the protocol created previously.
• Task 3 : Link the psychophysical results with a distance function to predict human perception of 3D Gaussian non-uniform aspect.

Références bibliographiques / Bibliography

[1] H. Chatoux, N. Richard, and S. Farnand, “How well do human perceive non-uniform surface noise variation?,” in CIE Midterm Meeting Vienna 2025, 2025.

[2] M. Giesel, T. Hansen, and K. R. Gegenfurtner, “The discrimination of chromatic textures,” Journal of Vision, 2009.

[3] R. Huertas, M. Melgosa, and E. Hita, “Influence of random-dot textures on perception of suprathreshold color differences,” Journal of the Optical Society of America A, 2006.

[4] F. Devinck and K. Knoblauch, “Color appearance of spatial patterns compared by direct estimation and conjoint measurement,” Journal of the Optical Society of America A, 2023.

Imagerie et Vision Artificielle

Conception de systèmes de vision, analyse d'images temps réel, aide au diagnostic médical, IA pour l'analyse de signaux et d'images, systèmes d'imagerie multi-modale et non conventionnelle, modélisation de l'apparence, perception pour/par la robotique, commande robotique.

The ideal candidate has Master in physics, information theory, cognitive psychology or computer science, preferably with some majors in color science or/and psychophysics. Other profiles may be considered case by case.

Preferred selection criteria:

• Knowledge in: Color and/or Psychophysics.
• Knowledge in: Python, especially Psycho-py
• Knowledge in:  Experimental design, Design of Experiment
• Excellent communication skills in written and oral English.

Personal characteristics:

•  Enthusiasm for experimentation, instrumentation, teamwork, and capability of independent problem solving.
• Ability to work individually and a high level of personal responsibility.
• Ability to meet deadlines and produce work of a consistently high standard.
• Eager to disseminate research results through publications and presentations at both academic and industrial international conferences.