Method of synthesis of abstract images with high self-similarity

Nikolay V. Matveev; Sergey A. Shcheglov; Galina E. Romanova; Тatiana A. Koneva

doi:10.1117/12.2270090

26 June 2017 Method of synthesis of abstract images with high self-similarity

Nikolay V. Matveev, Sergey A. Shcheglov, Galina E. Romanova, Тatiana A. Koneva

Proceedings Volume 10335, Digital Optical Technologies 2017; 103351N (2017) https://doi.org/10.1117/12.2270090
Event: SPIE Digital Optical Technologies, 2017, Munich, Germany

Abstract

Abstract images with high self-similarity could be used for drug-free stress therapy. This based on the fact that a complex visual environment has a high affective appraisal. To create such an image we can use the setup based on the three laser sources of small power and different colors (Red, Green, Blue), the image is the pattern resulting from the reflecting and refracting by the complicated form object placed into the laser ray paths. The images were obtained experimentally which showed the good therapy effect. However, to find and to choose the object which gives needed image structure is very difficult and requires many trials. The goal of the work is to develop a method and a procedure of finding the object form which if placed into the ray paths can provide the necessary structure of the image In fact the task means obtaining the necessary irradiance distribution on the given surface. Traditionally such problems are solved using the non-imaging optics methods. In the given case this task is very complicated because of the complicated structure of the illuminance distribution and its high non-linearity. Alternative way is to use the projected image of a mask with a given structure. We consider both ways and discuss how they can help to speed up the synthesis procedure for the given abstract image of the high self-similarity for the setups of drug-free therapy.

Citation Download Citation

Nikolay V. Matveev, Sergey A. Shcheglov, Galina E. Romanova, and Тatiana A. Koneva "Method of synthesis of abstract images with high self-similarity", Proc. SPIE 10335, Digital Optical Technologies 2017, 103351N (26 June 2017); https://doi.org/10.1117/12.2270090

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