Analysis of healing effects caused by changes in display resolution using biosensors

Author(s):  
Miho Shinohara ◽  
Mitsuho Yamada ◽  
Yuko Hoshino
Keyword(s):  
Author(s):  
Wenxuan Jia ◽  
Yuen-Shan Leung ◽  
Huachao Mao ◽  
Han Xu ◽  
Chi Zhou ◽  
...  

Abstract Microscale surface structures are commonly found on macroscale bodies of natural creatures for their unique functions. However, it is difficult to fabricate such multi-scale geometry with conventional stereolithography processes that rely on either laser or digital micromirror device (DMD). More specifically, the DMD-based mask projection method displays the image of a cross-section of the part on the resin to fabricate the entire layer efficiently; however, its display resolution is limited by the building area. In comparison, the laser-based vector scanning method builds smooth features using a focused laser beam with desired beam-width resolution; however, it has less throughput for its sequential nature. In this paper, we studied the hybrid-light-source stereolithography process that integrates both optical light sources to facilitate the fabrication of macro-objects with microscale surface structures (called micro-textures in the paper). The hardware system uses a novel calibration approach that ensures pixel-level dimensional accuracy across the two light sources. The software system enables designing the distribution and density of specific microscale textures on a macro-object by generating projection images and laser toolpaths for the two integrated light sources. Several test cases were fabricated to demonstrate the capability of the developed process. A large fabrication area (76.8 mm × 80.0 mm) with 50 μm micro-features can be achieved with a high throughput.


Author(s):  
James Shearer ◽  
Michael Ogawa ◽  
Kwan-Liu Ma ◽  
Toby Kohlenberg
Keyword(s):  

Author(s):  
Kiyomi Sakamoto ◽  
Seiji Sakashita ◽  
Hiroaki Shimazaki ◽  
Masahiro Kawashima ◽  
Kuniko Yamashita ◽  
...  

2000 ◽  
Vol 8 (7) ◽  
pp. 31-31
Author(s):  
Robert Meyer

To those scientists and researchers who use microscopes with video or digital cameras for the purpose of capture and display, there has always existed a fundamental problem, namely, imaging large tissue samples at high resolution.For some time, conventional technology has allowed video cameras to be attached to microscopes. The signal generated by these cameras can be captured and saved to a computer's hard drive using a frame grabber. A typical image capture and display resolution is 640 by 480 (307,200) pixels. Although the image produced is ‘good’, it is by no means considered ‘high resolution’. For the sake of discussion, ‘high resolution’ is defined as greater than 1,000 x 1,000 (1,000,000) pixels. High resolution images are essential for medical applications. Today's modern digital cameras can meet or exceed this value. The human eye, if compared to these examples, has the equivalent resolution of greater than 5,000 x 5,000 (25,000,000) pixels.


2010 ◽  
Vol 29 (4) ◽  
pp. 1-8 ◽  
Author(s):  
Piotr Didyk ◽  
Elmar Eisemann ◽  
Tobias Ritschel ◽  
Karol Myszkowski ◽  
Hans-Peter Seidel

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Siwei Wu ◽  
Shan Xiao ◽  
Yihua Di ◽  
Cheng Di

In this paper, the latest virtual reconstruction technology is used to conduct in-depth research on 3D movie animation image acquisition and feature processing. This paper firstly proposes a time-division multiplexing method based on subpixel multiplexing technology to improve the resolution of integrated imaging reconstruction images. By studying the degradation effect of the reconstruction process of the 3D integrated imaging system, it is proposed to improve the display resolution by increasing the pixel point information of fixed display array units. According to the subpixel multiplexing, an algorithm to realize the reuse of pixel point information of 3D scene element image gets the element image array with new information; then, through the high frame rate light emitting diode (LED) large screen fast output of the element image array, the human eye temporary retention effect is used, so that this group of element image array information go through a plane display, to increase the limited display array information capacity thus improving the reconstructed image. In this way, the information capacity of the finite display array is increased and the display resolution of the reconstructed image is improved. In this paper, we first use the classification algorithm to determine the gender and expression attributes of the face in the input image and filter the corresponding 3D face data subset in the database according to the gender and expression attributes, then use the sparse representation theory to filter the prototype face like the target face in the data subset, then use the filtered prototype face samples to construct the sparse deformation model, and finally use the target faces. Finally, the target 3D face is reconstructed using the feature points of the target face for model matching. The experimental results show that the algorithm reconstructs faces with high realism and accuracy, and the algorithm can reconstruct expression faces.


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