Prediction of the layered ink layout for 3D printers considering a desired skin color and line spread function

Nagasawa, Kazuki; Yoshii, J.; Yamamoto, Shoji; Arai, Wataru; Kaneko, Satoshi; Hirai, Keita; Tsumura, Norimichi

doi:10.1007/s10043-021-00679-z

Cited by 4 publications

(4 citation statements)

References 24 publications

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“…This approach involved taking a painting and utilizing mixed-integer programming to detect optimal inks for spectral reproduction. Nagasawa et al [12] introduced a method for determining skin color and translucency using the line spread function and NN. This method generated multi-layered color patches of human skin, computed the line spread function, and employed NN to estimate the layout.…”

Section: ░ 2 Literature Surveymentioning

confidence: 99%

A Novel Optimized Neural Network Model for Ink Selection in Printed Electronics

Narayanan,

Pillai

2023

IJEER

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The field of Printed Electronics (PE) is experiencing significant growth in the industrial sector and generating considerable interest across various industries due to its ability to produce intricate components. The functionality of printed electronic products heavily relies on the utilization of conductive ink during the printing process, which plays a vital role in developing flexible electronic circuits and improving the communicative functionalities of objects. Selecting the right ink for printing is crucial to meet consumer requirements. However, the conventional approach to this process has been manual, labor-intensive, and time-consuming, relying on the expertise of designers. This paper presents an automated ink selection model for printed circuits. This novel method has been incorporated with Multilayer Perceptron Neural Network (MLPNN) and Particle Swarm Optimization (PSO), named PSO-MLPNN. A dataset containing material features is generated by gathering information from both literature and experimental observations. To ensure uniformity, the data undergoes preprocessing using the min-max method, which scales all features to a standardized range between 0 and 1. A four-layer MLPNN is constructed to choose the most suitable ink. The network is trained with the PSO algorithm. The bias and weight values of MLPNN are tuned using the PSO algorithm to attain high accuracy. The computed findings confirm that the ink selection is highly effective and more accurate when compared to both the standard MLPNN.

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Section: ░ 2 Literature Surveymentioning

confidence: 99%

A Novel Optimized Neural Network Model for Ink Selection in Printed Electronics

Narayanan,

Pillai

2023

IJEER

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“…There are studies that reproduce arbitrarily the line spread function using multilayered inks with optimized layouts, restricting the modeling object to human skin [23]. Nagasawa et al proposed a method of reproducing the line spread function as an index of arbitrary skin tone and translucency by representing the epidermal and dermal layers, which are components of human skin, as thin layers of ink and varying the number of each type of layer (i.e., thickness).…”

Section: Fabrication Of Translucencymentioning

confidence: 99%

Perceptual Translucency in 3D Printing Using Surface Texture

Nagasawa

Ono

Arai³

et al. 2023

J. Imaging

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We propose a method of reproducing perceptual translucency in three-dimensional printing. In contrast to most conventional methods, which reproduce the physical properties of translucency, we focus on the perceptual aspects of translucency. Humans are known to rely on simple cues to perceive translucency, and we develop a method of reproducing these cues using the gradation of surface textures. Textures are designed to reproduce the intensity distribution of the shading and thus provide a cue for the perception of translucency. In creating textures, we adopt computer graphics to develop an image-based optimization method. We validate the effectiveness of the method through subjective evaluation experiments using three-dimensionally printed objects. The results of the validation suggest that the proposed method using texture may increase perceptual translucency under specific conditions. As a method for translucent 3D printing, our method has the limitation that it depends on the observation conditions; however, it provides knowledge to the field of perception that the human visual system can be cheated by only surface textures.

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“…We referred to the method of Nagasawa et al, which predicts an appropriate multilayer ink layout for reproducing the texture of human skin by layering translucent ink [ 24 ]. They used the line spread function (LSF) measured from the skin created as a measure of translucency and used a neural network to estimate the layout.…”

Section: Previous Workmentioning

confidence: 99%

“…As already mentioned above, skin is a multilayered structure with different pigments in each layer, and there are studies that have attempted to reproduce this structure in 3D printing. One study used multilayered skin modeling performed with a neural network-based method to estimate the optimal layer structure layout for reproducing human skin with arbitrary skin color and transparency [ 24 ]. Furthermore, a study has succeeded in reducing the fabrication cost by using simulation data [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

Fabrication of a Human Skin Mockup with a Multilayered Concentration Map of Pigment Components Using a UV Printer

Nagasawa

Yamamoto

Arai³

et al. 2022

J. Imaging

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In this paper, we propose a pipeline that reproduces human skin mockups using a UV printer by obtaining the spatial concentration map of pigments from an RGB image of human skin. The pigment concentration distributions were obtained by a separating method of skin pigment components with independent component analysis from the skin image. This method can extract the concentration of melanin and hemoglobin components, which are the main pigments that make up skin tone. Based on this concentration, we developed a procedure to reproduce a skin mockup with a multi-layered structure that is determined by mapping the absorbance of melanin and hemoglobin to CMYK (Cyan, Magenta, Yellow, Black) subtractive color mixing. In our proposed method, the multi-layered structure with different pigments in each layer contributes greatly to the accurate reproduction of skin tones. We use a UV printer because the printer is capable of layered fabrication by using UV-curable inks. As the result, subjective evaluation showed that the artificial skin reproduced by our method has a more skin-like appearance than that produced using conventional printing.

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Prediction of the layered ink layout for 3D printers considering a desired skin color and line spread function

Cited by 4 publications

References 24 publications

A Novel Optimized Neural Network Model for Ink Selection in Printed Electronics

A Novel Optimized Neural Network Model for Ink Selection in Printed Electronics

Perceptual Translucency in 3D Printing Using Surface Texture

Fabrication of a Human Skin Mockup with a Multilayered Concentration Map of Pigment Components Using a UV Printer

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